Sample records for object recognition model

  1. Interactive object recognition assistance: an approach to recognition starting from target objects

    NASA Astrophysics Data System (ADS)

    Geisler, Juergen; Littfass, Michael

    1999-07-01

    Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

  2. Trajectory Recognition as the Basis for Object Individuation: A Functional Model of Object File Instantiation and Object-Token Encoding

    PubMed Central

    Fields, Chris

    2011-01-01

    The perception of persisting visual objects is mediated by transient intermediate representations, object files, that are instantiated in response to some, but not all, visual trajectories. The standard object file concept does not, however, provide a mechanism sufficient to account for all experimental data on visual object persistence, object tracking, and the ability to perceive spatially disconnected stimuli as continuously existing objects. Based on relevant anatomical, functional, and developmental data, a functional model is constructed that bases visual object individuation on the recognition of temporal sequences of apparent center-of-mass positions that are specifically identified as trajectories by dedicated “trajectory recognition networks” downstream of the medial–temporal motion-detection area. This model is shown to account for a wide range of data, and to generate a variety of testable predictions. Individual differences in the recognition, abstraction, and encoding of trajectory information are expected to generate distinct object persistence judgments and object recognition abilities. Dominance of trajectory information over feature information in stored object tokens during early infancy, in particular, is expected to disrupt the ability to re-identify human and other individuals across perceptual episodes, and lead to developmental outcomes with characteristics of autism spectrum disorders. PMID:21716599

  3. Object recognition in images via a factor graph model

    NASA Astrophysics Data System (ADS)

    He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

    2018-04-01

    Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

  4. Three-dimensional model-based object recognition and segmentation in cluttered scenes.

    PubMed

    Mian, Ajmal S; Bennamoun, Mohammed; Owens, Robyn

    2006-10-01

    Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based algorithm which performs this task automatically and efficiently. A 3D model of an object is automatically constructed offline from its multiple unordered range images (views). These views are converted into multidimensional table representations (which we refer to as tensors). Correspondences are automatically established between these views by simultaneously matching the tensors of a view with those of the remaining views using a hash table-based voting scheme. This results in a graph of relative transformations used to register the views before they are integrated into a seamless 3D model. These models and their tensor representations constitute the model library. During online recognition, a tensor from the scene is simultaneously matched with those in the library by casting votes. Similarity measures are calculated for the model tensors which receive the most votes. The model with the highest similarity is transformed to the scene and, if it aligns accurately with an object in the scene, that object is declared as recognized and is segmented. This process is repeated until the scene is completely segmented. Experiments were performed on real and synthetic data comprised of 55 models and 610 scenes and an overall recognition rate of 95 percent was achieved. Comparison with the spin images revealed that our algorithm is superior in terms of recognition rate and efficiency.

  5. Modeling guidance and recognition in categorical search: bridging human and computer object detection.

    PubMed

    Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

    2013-10-08

    Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

  6. Modeling guidance and recognition in categorical search: Bridging human and computer object detection

    PubMed Central

    Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

    2013-01-01

    Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery. PMID:24105460

  7. Orientation congruency effects for familiar objects: coordinate transformations in object recognition.

    PubMed

    Graf, M; Kaping, D; Bülthoff, H H

    2005-03-01

    How do observers recognize objects after spatial transformations? Recent neurocomputational models have proposed that object recognition is based on coordinate transformations that align memory and stimulus representations. If the recognition of a misoriented object is achieved by adjusting a coordinate system (or reference frame), then recognition should be facilitated when the object is preceded by a different object in the same orientation. In the two experiments reported here, two objects were presented in brief masked displays that were in close temporal contiguity; the objects were in either congruent or incongruent picture-plane orientations. Results showed that naming accuracy was higher for congruent than for incongruent orientations. The congruency effect was independent of superordinate category membership (Experiment 1) and was found for objects with different main axes of elongation (Experiment 2). The results indicate congruency effects for common familiar objects even when they have dissimilar shapes. These findings are compatible with models in which object recognition is achieved by an adjustment of a perceptual coordinate system.

  8. A biologically plausible computational model for auditory object recognition.

    PubMed

    Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

    2009-01-01

    Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

  9. Cognitive object recognition system (CORS)

    NASA Astrophysics Data System (ADS)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  10. Infant visual attention and object recognition.

    PubMed

    Reynolds, Greg D

    2015-05-15

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Infant Visual Attention and Object Recognition

    PubMed Central

    Reynolds, Greg D.

    2015-01-01

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. PMID:25596333

  12. Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

    PubMed

    Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

    2013-08-01

    Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

  13. Short temporal asynchrony disrupts visual object recognition

    PubMed Central

    Singer, Jedediah M.; Kreiman, Gabriel

    2014-01-01

    Humans can recognize objects and scenes in a small fraction of a second. The cascade of signals underlying rapid recognition might be disrupted by temporally jittering different parts of complex objects. Here we investigated the time course over which shape information can be integrated to allow for recognition of complex objects. We presented fragments of object images in an asynchronous fashion and behaviorally evaluated categorization performance. We observed that visual recognition was significantly disrupted by asynchronies of approximately 30 ms, suggesting that spatiotemporal integration begins to break down with even small deviations from simultaneity. However, moderate temporal asynchrony did not completely obliterate recognition; in fact, integration of visual shape information persisted even with an asynchrony of 100 ms. We describe the data with a concise model based on the dynamic reduction of uncertainty about what image was presented. These results emphasize the importance of timing in visual processing and provide strong constraints for the development of dynamical models of visual shape recognition. PMID:24819738

  14. Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

    PubMed

    Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

    2017-01-01

    Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

  15. Toward a unified model of face and object recognition in the human visual system

    PubMed Central

    Wallis, Guy

    2013-01-01

    Our understanding of the mechanisms and neural substrates underlying visual recognition has made considerable progress over the past 30 years. During this period, accumulating evidence has led many scientists to conclude that objects and faces are recognised in fundamentally distinct ways, and in fundamentally distinct cortical areas. In the psychological literature, in particular, this dissociation has led to a palpable disconnect between theories of how we process and represent the two classes of object. This paper follows a trend in part of the recognition literature to try to reconcile what we know about these two forms of recognition by considering the effects of learning. Taking a widely accepted, self-organizing model of object recognition, this paper explains how such a system is affected by repeated exposure to specific stimulus classes. In so doing, it explains how many aspects of recognition generally regarded as unusual to faces (holistic processing, configural processing, sensitivity to inversion, the other-race effect, the prototype effect, etc.) are emergent properties of category-specific learning within such a system. Overall, the paper describes how a single model of recognition learning can and does produce the seemingly very different types of representation associated with faces and objects. PMID:23966963

  16. A rodent model for the study of invariant visual object recognition

    PubMed Central

    Zoccolan, Davide; Oertelt, Nadja; DiCarlo, James J.; Cox, David D.

    2009-01-01

    The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability—known as “invariant” object recognition—is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing. PMID:19429704

  17. Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration.

    PubMed

    Wang, Panqu; Gauthier, Isabel; Cottrell, Garrison

    2016-04-01

    Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing ["The Model", TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a "spreading transform" for faces (separating them in representational space) that

  18. Object recognition with hierarchical discriminant saliency networks.

    PubMed

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  19. A biologically inspired neural network model to transformation invariant object recognition

    NASA Astrophysics Data System (ADS)

    Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

    2007-09-01

    Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to

  20. Vision-based object detection and recognition system for intelligent vehicles

    NASA Astrophysics Data System (ADS)

    Ran, Bin; Liu, Henry X.; Martono, Wilfung

    1999-01-01

    Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

  1. Mechanisms of object recognition: what we have learned from pigeons

    PubMed Central

    Soto, Fabian A.; Wasserman, Edward A.

    2014-01-01

    Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the “simple” brains of pigeons. PMID:25352784

  2. Generalization between canonical and non-canonical views in object recognition

    PubMed Central

    Ghose, Tandra; Liu, Zili

    2013-01-01

    Viewpoint generalization in object recognition is the process that allows recognition of a given 3D object from many different viewpoints despite variations in its 2D projections. We used the canonical view effects as a foundation to empirically test the validity of a major theory in object recognition, the view-approximation model (Poggio & Edelman, 1990). This model predicts that generalization should be better when an object is first seen from a non-canonical view and then a canonical view than when seen in the reversed order. We also manipulated object similarity to study the degree to which this view generalization was constrained by shape details and task instructions (object vs. image recognition). Old-new recognition performance for basic and subordinate level objects was measured in separate blocks. We found that for object recognition, view generalization between canonical and non-canonical views was comparable for basic level objects. For subordinate level objects, recognition performance was more accurate from non-canonical to canonical views than the other way around. When the task was changed from object recognition to image recognition, the pattern of the results reversed. Interestingly, participants responded “old” to “new” images of “old” objects with a substantially higher rate than to “new” objects, despite instructions to the contrary, thereby indicating involuntary view generalization. Our empirical findings are incompatible with the prediction of the view-approximation theory, and argue against the hypothesis that views are stored independently. PMID:23283692

  3. Hierachical Object Recognition Using Libraries of Parameterized Model Sub-Parts.

    DTIC Science & Technology

    1987-06-01

    SketchI Structure Hierarchy Constrained Search 20. AUISTR ACT (Ce.ntU..w se reveres. 01411 at 00 OW 4MI 9smtilp Me"h aindo" This thesis describes the... theseU hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to...with different relative scaling, rotation, or translation than in the models. The approach taken in this thesis is to develop an object shape

  4. Integration trumps selection in object recognition.

    PubMed

    Saarela, Toni P; Landy, Michael S

    2015-03-30

    Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Integration trumps selection in object recognition

    PubMed Central

    Saarela, Toni P.; Landy, Michael S.

    2015-01-01

    Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

  6. Shape and Color Features for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

    2012-01-01

    A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

  7. A new selective developmental deficit: Impaired object recognition with normal face recognition.

    PubMed

    Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

    2011-05-01

    Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

  8. Comparison of Object Recognition Behavior in Human and Monkey

    PubMed Central

    Rajalingham, Rishi; Schmidt, Kailyn

    2015-01-01

    Although the rhesus monkey is used widely as an animal model of human visual processing, it is not known whether invariant visual object recognition behavior is quantitatively comparable across monkeys and humans. To address this question, we systematically compared the core object recognition behavior of two monkeys with that of human subjects. To test true object recognition behavior (rather than image matching), we generated several thousand naturalistic synthetic images of 24 basic-level objects with high variation in viewing parameters and image background. Monkeys were trained to perform binary object recognition tasks on a match-to-sample paradigm. Data from 605 human subjects performing the same tasks on Mechanical Turk were aggregated to characterize “pooled human” object recognition behavior, as well as 33 separate Mechanical Turk subjects to characterize individual human subject behavior. Our results show that monkeys learn each new object in a few days, after which they not only match mean human performance but show a pattern of object confusion that is highly correlated with pooled human confusion patterns and is statistically indistinguishable from individual human subjects. Importantly, this shared human and monkey pattern of 3D object confusion is not shared with low-level visual representations (pixels, V1+; models of the retina and primary visual cortex) but is shared with a state-of-the-art computer vision feature representation. Together, these results are consistent with the hypothesis that rhesus monkeys and humans share a common neural shape representation that directly supports object perception. SIGNIFICANCE STATEMENT To date, several mammalian species have shown promise as animal models for studying the neural mechanisms underlying high-level visual processing in humans. In light of this diversity, making tight comparisons between nonhuman and human primates is particularly critical in determining the best use of nonhuman primates to

  9. Three-dimensional object recognition based on planar images

    NASA Astrophysics Data System (ADS)

    Mital, Dinesh P.; Teoh, Eam-Khwang; Au, K. C.; Chng, E. K.

    1993-01-01

    This paper presents the development and realization of a robotic vision system for the recognition of 3-dimensional (3-D) objects. The system can recognize a single object from among a group of known regular convex polyhedron objects that is constrained to lie on a calibrated flat platform. The approach adopted comprises a series of image processing operations on a single 2-dimensional (2-D) intensity image to derive an image line drawing. Subsequently, a feature matching technique is employed to determine 2-D spatial correspondences of the image line drawing with the model in the database. Besides its identification ability, the system can also provide important position and orientation information of the recognized object. The system was implemented on an IBM-PC AT machine executing at 8 MHz without the 80287 Maths Co-processor. In our overall performance evaluation based on a 600 recognition cycles test, the system demonstrated an accuracy of above 80% with recognition time well within 10 seconds. The recognition time is, however, indirectly dependent on the number of models in the database. The reliability of the system is also affected by illumination conditions which must be clinically controlled as in any industrial robotic vision system.

  10. Parallel and distributed computation for fault-tolerant object recognition

    NASA Technical Reports Server (NTRS)

    Wechsler, Harry

    1988-01-01

    The distributed associative memory (DAM) model is suggested for distributed and fault-tolerant computation as it relates to object recognition tasks. The fault-tolerance is with respect to geometrical distortions (scale and rotation), noisy inputs, occulsion/overlap, and memory faults. An experimental system was developed for fault-tolerant structure recognition which shows the feasibility of such an approach. The approach is futher extended to the problem of multisensory data integration and applied successfully to the recognition of colored polyhedral objects.

  11. Figure-ground organization and object recognition processes: an interactive account.

    PubMed

    Vecera, S P; O'Reilly, R C

    1998-04-01

    Traditional bottom-up models of visual processing assume that figure-ground organization precedes object recognition. This assumption seems logically necessary: How can object recognition occur before a region is labeled as figure? However, some behavioral studies find that familiar regions are more likely to be labeled figure than less familiar regions, a problematic finding for bottom-up models. An interactive account is proposed in which figure-ground processes receive top-down input from object representations in a hierarchical system. A graded, interactive computational model is presented that accounts for behavioral results in which familiarity effects are found. The interactive model offers an alternative conception of visual processing to bottom-up models.

  12. Ball-scale based hierarchical multi-object recognition in 3D medical images

    NASA Astrophysics Data System (ADS)

    Bağci, Ulas; Udupa, Jayaram K.; Chen, Xinjian

    2010-03-01

    This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.

  13. Method and System for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  14. Orientation estimation of anatomical structures in medical images for object recognition

    NASA Astrophysics Data System (ADS)

    Bağci, Ulaş; Udupa, Jayaram K.; Chen, Xinjian

    2011-03-01

    Recognition of anatomical structures is an important step in model based medical image segmentation. It provides pose estimation of objects and information about "where" roughly the objects are in the image and distinguishing them from other object-like entities. In,1 we presented a general method of model-based multi-object recognition to assist in segmentation (delineation) tasks. It exploits the pose relationship that can be encoded, via the concept of ball scale (b-scale), between the binary training objects and their associated grey images. The goal was to place the model, in a single shot, close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. Unlike position and scale parameters, we observe that orientation parameters require more attention when estimating the pose of the model as even small differences in orientation parameters can lead to inappropriate recognition. Motivated from the non-Euclidean nature of the pose information, we propose in this paper the use of non-Euclidean metrics to estimate orientation of the anatomical structures for more accurate recognition and segmentation. We statistically analyze and evaluate the following metrics for orientation estimation: Euclidean, Log-Euclidean, Root-Euclidean, Procrustes Size-and-Shape, and mean Hermitian metrics. The results show that mean Hermitian and Cholesky decomposition metrics provide more accurate orientation estimates than other Euclidean and non-Euclidean metrics.

  15. Sensor agnostic object recognition using a map seeking circuit

    NASA Astrophysics Data System (ADS)

    Overman, Timothy L.; Hart, Michael

    2012-05-01

    Automatic object recognition capabilities are traditionally tuned to exploit the specific sensing modality they were designed to. Their successes (and shortcomings) are tied to object segmentation from the background, they typically require highly skilled personnel to train them, and they become cumbersome with the introduction of new objects. In this paper we describe a sensor independent algorithm based on the biologically inspired technology of map seeking circuits (MSC) which overcomes many of these obstacles. In particular, the MSC concept offers transparency in object recognition from a common interface to all sensor types, analogous to a USB device. It also provides a common core framework that is independent of the sensor and expandable to support high dimensionality decision spaces. Ease in training is assured by using commercially available 3D models from the video game community. The search time remains linear no matter how many objects are introduced, ensuring rapid object recognition. Here, we report results of an MSC algorithm applied to object recognition and pose estimation from high range resolution radar (1D), electrooptical imagery (2D), and LIDAR point clouds (3D) separately. By abstracting the sensor phenomenology from the underlying a prior knowledge base, MSC shows promise as an easily adaptable tool for incorporating additional sensor inputs.

  16. Neural-Network Object-Recognition Program

    NASA Technical Reports Server (NTRS)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  17. Perceptual Plasticity for Auditory Object Recognition

    PubMed Central

    Heald, Shannon L. M.; Van Hedger, Stephen C.; Nusbaum, Howard C.

    2017-01-01

    In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as “noise” in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples

  18. The role of perceptual load in object recognition.

    PubMed

    Lavie, Nilli; Lin, Zhicheng; Zokaei, Nahid; Thoma, Volker

    2009-10-01

    Predictions from perceptual load theory (Lavie, 1995, 2005) regarding object recognition across the same or different viewpoints were tested. Results showed that high perceptual load reduces distracter recognition levels despite always presenting distracter objects from the same view. They also showed that the levels of distracter recognition were unaffected by a change in the distracter object view under conditions of low perceptual load. These results were found both with repetition priming measures of distracter recognition and with performance on a surprise recognition memory test. The results support load theory proposals that distracter recognition critically depends on the level of perceptual load. The implications for the role of attention in object recognition theories are discussed. PsycINFO Database Record (c) 2009 APA, all rights reserved.

  19. Eye movements during object recognition in visual agnosia.

    PubMed

    Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe

    2012-07-01

    This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Coordinate Transformations in Object Recognition

    ERIC Educational Resources Information Center

    Graf, Markus

    2006-01-01

    A basic problem of visual perception is how human beings recognize objects after spatial transformations. Three central classes of findings have to be accounted for: (a) Recognition performance varies systematically with orientation, size, and position; (b) recognition latencies are sequentially additive, suggesting analogue transformation…

  1. Invariant visual object recognition and shape processing in rats

    PubMed Central

    Zoccolan, Davide

    2015-01-01

    Invariant visual object recognition is the ability to recognize visual objects despite the vastly different images that each object can project onto the retina during natural vision, depending on its position and size within the visual field, its orientation relative to the viewer, etc. Achieving invariant recognition represents such a formidable computational challenge that is often assumed to be a unique hallmark of primate vision. Historically, this has limited the invasive investigation of its neuronal underpinnings to monkey studies, in spite of the narrow range of experimental approaches that these animal models allow. Meanwhile, rodents have been largely neglected as models of object vision, because of the widespread belief that they are incapable of advanced visual processing. However, the powerful array of experimental tools that have been developed to dissect neuronal circuits in rodents has made these species very attractive to vision scientists too, promoting a new tide of studies that have started to systematically explore visual functions in rats and mice. Rats, in particular, have been the subjects of several behavioral studies, aimed at assessing how advanced object recognition and shape processing is in this species. Here, I review these recent investigations, as well as earlier studies of rat pattern vision, to provide an historical overview and a critical summary of the status of the knowledge about rat object vision. The picture emerging from this survey is very encouraging with regard to the possibility of using rats as complementary models to monkeys in the study of higher-level vision. PMID:25561421

  2. Object location and object recognition memory impairments, motivation deficits and depression in a model of Gulf War illness.

    PubMed

    Hattiangady, Bharathi; Mishra, Vikas; Kodali, Maheedhar; Shuai, Bing; Rao, Xiolan; Shetty, Ashok K

    2014-01-01

    Memory and mood deficits are the enduring brain-related symptoms in Gulf War illness (GWI). Both animal model and epidemiological investigations have indicated that these impairments in a majority of GW veterans are linked to exposures to chemicals such as pyridostigmine bromide (PB, an antinerve gas drug), permethrin (PM, an insecticide) and DEET (a mosquito repellant) encountered during the Persian Gulf War-1. Our previous study in a rat model has shown that combined exposures to low doses of GWI-related (GWIR) chemicals PB, PM, and DEET with or without 5-min of restraint stress (a mild stress paradigm) causes hippocampus-dependent spatial memory dysfunction in a water maze test (WMT) and increased depressive-like behavior in a forced swim test (FST). In this study, using a larger cohort of rats exposed to GWIR-chemicals and stress, we investigated whether the memory deficiency identified earlier in a WMT is reproducible with an alternative and stress free hippocampus-dependent memory test such as the object location test (OLT). We also ascertained the possible co-existence of hippocampus-independent memory dysfunction using a novel object recognition test (NORT), and alterations in mood function with additional tests for motivation and depression. Our results provide new evidence that exposure to low doses of GWIR-chemicals and mild stress for 4 weeks causes deficits in hippocampus-dependent object location memory and perirhinal cortex-dependent novel object recognition memory. An open field test performed prior to other behavioral analyses revealed that memory impairments were not associated with increased anxiety or deficits in general motor ability. However, behavioral tests for mood function such as a voluntary physical exercise paradigm and a novelty suppressed feeding test (NSFT) demonstrated decreased motivation levels and depression. Thus, exposure to GWIR-chemicals and stress causes both hippocampus-dependent and hippocampus-independent memory

  3. Non-accidental properties, metric invariance, and encoding by neurons in a model of ventral stream visual object recognition, VisNet.

    PubMed

    Rolls, Edmund T; Mills, W Patrick C

    2018-05-01

    When objects transform into different views, some properties are maintained, such as whether the edges are convex or concave, and these non-accidental properties are likely to be important in view-invariant object recognition. The metric properties, such as the degree of curvature, may change with different views, and are less likely to be useful in object recognition. It is shown that in a model of invariant visual object recognition in the ventral visual stream, VisNet, non-accidental properties are encoded much more than metric properties by neurons. Moreover, it is shown how with the temporal trace rule training in VisNet, non-accidental properties of objects become encoded by neurons, and how metric properties are treated invariantly. We also show how VisNet can generalize between different objects if they have the same non-accidental property, because the metric properties are likely to overlap. VisNet is a 4-layer unsupervised model of visual object recognition trained by competitive learning that utilizes a temporal trace learning rule to implement the learning of invariance using views that occur close together in time. A second crucial property of this model of object recognition is, when neurons in the level corresponding to the inferior temporal visual cortex respond selectively to objects, whether neurons in the intermediate layers can respond to combinations of features that may be parts of two or more objects. In an investigation using the four sides of a square presented in every possible combination, it was shown that even though different layer 4 neurons are tuned to encode each feature or feature combination orthogonally, neurons in the intermediate layers can respond to features or feature combinations present is several objects. This property is an important part of the way in which high capacity can be achieved in the four-layer ventral visual cortical pathway. These findings concerning non-accidental properties and the use of neurons in

  4. Object and event recognition for stroke rehabilitation

    NASA Astrophysics Data System (ADS)

    Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.

    2003-06-01

    Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

  5. Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

    NASA Astrophysics Data System (ADS)

    Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

    2016-06-01

    An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

  6. Object instance recognition using motion cues and instance specific appearance models

    NASA Astrophysics Data System (ADS)

    Schumann, Arne

    2014-03-01

    In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

  7. Object memory effects on figure assignment: conscious object recognition is not necessary or sufficient.

    PubMed

    Peterson, M A; de Gelder, B; Rapcsak, S Z; Gerhardstein, P C; Bachoud-Lévi, A

    2000-01-01

    In three experiments we investigated whether conscious object recognition is necessary or sufficient for effects of object memories on figure assignment. In experiment 1, we examined a brain-damaged participant, AD, whose conscious object recognition is severely impaired. AD's responses about figure assignment do reveal effects from memories of object structure, indicating that conscious object recognition is not necessary for these effects, and identifying the figure-ground test employed here as a new implicit test of access to memories of object structure. In experiments 2 and 3, we tested a second brain-damaged participant, WG, for whom conscious object recognition was relatively spared. Nevertheless, effects from memories of object structure on figure assignment were not evident in WG's responses about figure assignment in experiment 2, indicating that conscious object recognition is not sufficient for effects of object memories on figure assignment. WG's performance sheds light on AD's performance, and has implications for the theoretical understanding of object memory effects on figure assignment.

  8. Hippocampal histone acetylation regulates object recognition and the estradiol-induced enhancement of object recognition

    PubMed Central

    Zhao, Zaorui; Fan, Lu; Fortress, Ashley M.; Boulware, Marissa I.; Frick, Karyn M.

    2012-01-01

    Histone acetylation has recently been implicated in learning and memory processes, yet necessity of histone acetylation for such processes has not been demonstrated using pharmacological inhibitors of histone acetyltransferases (HATs). As such, the present study tested whether garcinol, a potent HAT inhibitor in vitro, could impair hippocampal memory consolidation and block the memory-enhancing effects of the modulatory hormone 17β-estradiol (E2). We first showed that bilateral infusion of garcinol (0.1, 1, or 10 μg/side) into the dorsal hippocampus (DH) immediately after training impaired object recognition memory consolidation in ovariectomized female mice. A behaviorally effective dose of garcinol (10 μg/side) also significantly decreased DH HAT activity. We next examined whether DH infusion of a behaviorally subeffective dose of garcinol (1 ng/side) could block the effects of DH E2 infusion on object recognition and epigenetic processes. Immediately after training, ovariectomized female mice received bilateral DH infusions of vehicle, E2 (5 μg/side), garcinol (1 ng/side), or E2 plus garcinol. Forty-eight hours later, garcinol blocked the memory-enhancing effects of E2. Garcinol also reversed the E2-induced increase in DH histone H3 acetylation, HAT activity, and levels of the de novo methyltransferase DNMT3B, as well as the E2-induced decrease in levels of the memory repressor protein histone deacetylase 2 (HDAC2). Collectively, these findings suggest that histone acetylation is critical for object recognition memory consolidation and the beneficial effects of E2 on object recognition. Importantly, this work demonstrates that the role of histone acetylation in memory processes can be studied using a HAT inhibitor. PMID:22396409

  9. The role of color information on object recognition: a review and meta-analysis.

    PubMed

    Bramão, Inês; Reis, Alexandra; Petersson, Karl Magnus; Faísca, Luís

    2011-09-01

    In this study, we systematically review the scientific literature on the effect of color on object recognition. Thirty-five independent experiments, comprising 1535 participants, were included in a meta-analysis. We found a moderate effect of color on object recognition (d=0.28). Specific effects of moderator variables were analyzed and we found that color diagnosticity is the factor with the greatest moderator effect on the influence of color in object recognition; studies using color diagnostic objects showed a significant color effect (d=0.43), whereas a marginal color effect was found in studies that used non-color diagnostic objects (d=0.18). The present study did not permit the drawing of specific conclusions about the moderator effect of the object recognition task; while the meta-analytic review showed that color information improves object recognition mainly in studies using naming tasks (d=0.36), the literature review revealed a large body of evidence showing positive effects of color information on object recognition in studies using a large variety of visual recognition tasks. We also found that color is important for the ability to recognize artifacts and natural objects, to recognize objects presented as types (line-drawings) or as tokens (photographs), and to recognize objects that are presented without surface details, such as texture or shadow. Taken together, the results of the meta-analysis strongly support the contention that color plays a role in object recognition. This suggests that the role of color should be taken into account in models of visual object recognition. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Automatic anatomy recognition via multiobject oriented active shape models.

    PubMed

    Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

    2010-12-01

    This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a

  11. Exploiting core knowledge for visual object recognition.

    PubMed

    Schurgin, Mark W; Flombaum, Jonathan I

    2017-03-01

    Humans recognize thousands of objects, and with relative tolerance to variable retinal inputs. The acquisition of this ability is not fully understood, and it remains an area in which artificial systems have yet to surpass people. We sought to investigate the memory process that supports object recognition. Specifically, we investigated the association of inputs that co-occur over short periods of time. We tested the hypothesis that human perception exploits expectations about object kinematics to limit the scope of association to inputs that are likely to have the same token as a source. In several experiments we exposed participants to images of objects, and we then tested recognition sensitivity. Using motion, we manipulated whether successive encounters with an image took place through kinematics that implied the same or a different token as the source of those encounters. Images were injected with noise, or shown at varying orientations, and we included 2 manipulations of motion kinematics. Across all experiments, memory performance was better for images that had been previously encountered with kinematics that implied a single token. A model-based analysis similarly showed greater memory strength when images were shown via kinematics that implied a single token. These results suggest that constraints from physics are built into the mechanisms that support memory about objects. Such constraints-often characterized as 'Core Knowledge'-are known to support perception and cognition broadly, even in young infants. But they have never been considered as a mechanism for memory with respect to recognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  12. SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

    PubMed Central

    Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

    2013-01-01

    Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

  13. General object recognition is specific: Evidence from novel and familiar objects.

    PubMed

    Richler, Jennifer J; Wilmer, Jeremy B; Gauthier, Isabel

    2017-09-01

    In tests of object recognition, individual differences typically correlate modestly but nontrivially across familiar categories (e.g. cars, faces, shoes, birds, mushrooms). In theory, these correlations could reflect either global, non-specific mechanisms, such as general intelligence (IQ), or more specific mechanisms. Here, we introduce two separate methods for effectively capturing category-general performance variation, one that uses novel objects and one that uses familiar objects. In each case, we show that category-general performance variance is unrelated to IQ, thereby implicating more specific mechanisms. The first approach examines three newly developed novel object memory tests (NOMTs). We predicted that NOMTs would exhibit more shared, category-general variance than familiar object memory tests (FOMTs) because novel objects, unlike familiar objects, lack category-specific environmental influences (e.g. exposure to car magazines or botany classes). This prediction held, and remarkably, virtually none of the substantial shared variance among NOMTs was explained by IQ. Also, while NOMTs correlated nontrivially with two FOMTs (faces, cars), these correlations were smaller than among NOMTs and no larger than between the face and car tests themselves, suggesting that the category-general variance captured by NOMTs is specific not only relative to IQ, but also, to some degree, relative to both face and car recognition. The second approach averaged performance across multiple FOMTs, which we predicted would increase category-general variance by averaging out category-specific factors. This prediction held, and as with NOMTs, virtually none of the shared variance among FOMTs was explained by IQ. Overall, these results support the existence of object recognition mechanisms that, though category-general, are specific relative to IQ and substantially separable from face and car recognition. They also add sensitive, well-normed NOMTs to the tools available to study

  14. Central administration of angiotensin IV rapidly enhances novel object recognition among mice

    PubMed Central

    Paris, Jason J.; Eans, Shainnel O.; Mizrachi, Elisa; Reilley, Kate J.; Ganno, Michelle L.; McLaughlin, Jay P.

    2013-01-01

    Angiotensin IV (Val1-Tyr2-Ile3-His4-Pro5-Phe6) has demonstrated potential cognitive-enhancing effects. The present investigation assessed and characterized: (1) dose-dependency of angiotensin IV's cognitive enhancement in a C57BL/6J mouse model of novel object recognition, (2) the time-course for these effects, (3) the identity of residues in the hexapeptide important to these effects and (4) the necessity of actions at angiotensin IV receptors for pro-cognitive activity. Assessment of C57BL/6J mice in a novel object recognition task demonstrated that prior administration of angiotensin IV (0.1, 1.0, or 10.0, but not 0.01, nmol, i.c.v.) significantly enhanced novel object recognition in a dose-dependent manner. These effects were time dependent, with improved novel object recognition observed when angiotensin IV (0.1 nmol, i.c.v.) was administered 10 or 20, but not 30, min prior to the onset of the novel object recognition testing. An alanine scan of the angiotensin IV peptide revealed that replacement of the Val1, Ile3, His4, or Phe6 residues with Ala attenuated peptide-induced improvements in novel object recognition, whereas Tyr2 or Pro5 replacement did not significantly affect performance. Administration of the angiotensin IV receptor antagonist, divalinal-Ang IV (20 nmol, i.c.v.), reduced (but did not abolish) novel object recognition; however, this antagonist completely blocked the pro-cognitive effects of angiotensin IV (0.1 nmol, i.c.v.) in this task. Rotorod testing demonstrated no locomotor effects for any angiotensin IV or divalinal-Ang IV dose tested. These data demonstrate that angiotensin IV produces a rapid enhancement of associative learning and memory performance in a mouse model that was dependent on the angiotensin IV receptor. PMID:23416700

  15. Central administration of angiotensin IV rapidly enhances novel object recognition among mice.

    PubMed

    Paris, Jason J; Eans, Shainnel O; Mizrachi, Elisa; Reilley, Kate J; Ganno, Michelle L; McLaughlin, Jay P

    2013-07-01

    Angiotensin IV (Val(1)-Tyr(2)-Ile(3)-His(4)-Pro(5)-Phe(6)) has demonstrated potential cognitive-enhancing effects. The present investigation assessed and characterized: (1) dose-dependency of angiotensin IV's cognitive enhancement in a C57BL/6J mouse model of novel object recognition, (2) the time-course for these effects, (3) the identity of residues in the hexapeptide important to these effects and (4) the necessity of actions at angiotensin IV receptors for procognitive activity. Assessment of C57BL/6J mice in a novel object recognition task demonstrated that prior administration of angiotensin IV (0.1, 1.0, or 10.0, but not 0.01 nmol, i.c.v.) significantly enhanced novel object recognition in a dose-dependent manner. These effects were time dependent, with improved novel object recognition observed when angiotensin IV (0.1 nmol, i.c.v.) was administered 10 or 20, but not 30 min prior to the onset of the novel object recognition testing. An alanine scan of the angiotensin IV peptide revealed that replacement of the Val(1), Ile(3), His(4), or Phe(6) residues with Ala attenuated peptide-induced improvements in novel object recognition, whereas Tyr(2) or Pro(5) replacement did not significantly affect performance. Administration of the angiotensin IV receptor antagonist, divalinal-Ang IV (20 nmol, i.c.v.), reduced (but did not abolish) novel object recognition; however, this antagonist completely blocked the procognitive effects of angiotensin IV (0.1 nmol, i.c.v.) in this task. Rotorod testing demonstrated no locomotor effects with any angiotensin IV or divalinal-Ang IV dose tested. These data demonstrate that angiotensin IV produces a rapid enhancement of associative learning and memory performance in a mouse model that was dependent on the angiotensin IV receptor. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Automatic anatomy recognition using neural network learning of object relationships via virtual landmarks

    NASA Astrophysics Data System (ADS)

    Yan, Fengxia; Udupa, Jayaram K.; Tong, Yubing; Xu, Guoping; Odhner, Dewey; Torigian, Drew A.

    2018-03-01

    The recently developed body-wide Automatic Anatomy Recognition (AAR) methodology depends on fuzzy modeling of individual objects, hierarchically arranging objects, constructing an anatomy ensemble of these models, and a dichotomous object recognition-delineation process. The parent-to-offspring spatial relationship in the object hierarchy is crucial in the AAR method. We have found this relationship to be quite complex, and as such any improvement in capturing this relationship information in the anatomy model will improve the process of recognition itself. Currently, the method encodes this relationship based on the layout of the geometric centers of the objects. Motivated by the concept of virtual landmarks (VLs), this paper presents a new one-shot AAR recognition method that utilizes the VLs to learn object relationships by training a neural network to predict the pose and the VLs of an offspring object given the VLs of the parent object in the hierarchy. We set up two neural networks for each parent-offspring object pair in a body region, one for predicting the VLs and another for predicting the pose parameters. The VL-based learning/prediction method is evaluated on two object hierarchies involving 14 objects. We utilize 54 computed tomography (CT) image data sets of head and neck cancer patients and the associated object contours drawn by dosimetrists for routine radiation therapy treatment planning. The VL neural network method is found to yield more accurate object localization than the currently used simple AAR method.

  17. The Role of Perceptual Load in Object Recognition

    ERIC Educational Resources Information Center

    Lavie, Nilli; Lin, Zhicheng; Zokaei, Nahid; Thoma, Volker

    2009-01-01

    Predictions from perceptual load theory (Lavie, 1995, 2005) regarding object recognition across the same or different viewpoints were tested. Results showed that high perceptual load reduces distracter recognition levels despite always presenting distracter objects from the same view. They also showed that the levels of distracter recognition were…

  18. Combining heterogenous features for 3D hand-held object recognition

    NASA Astrophysics Data System (ADS)

    Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

    2014-10-01

    Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

  19. Single prolonged stress impairs social and object novelty recognition in rats.

    PubMed

    Eagle, Andrew L; Fitzpatrick, Chris J; Perrine, Shane A

    2013-11-01

    Posttraumatic stress disorder (PTSD) results from exposure to a traumatic event and manifests as re-experiencing, arousal, avoidance, and negative cognition/mood symptoms. Avoidant symptoms, as well as the newly defined negative cognitions/mood, are a serious complication leading to diminished interest in once important or positive activities, such as social interaction; however, the basis of these symptoms remains poorly understood. PTSD patients also exhibit impaired object and social recognition, which may underlie the avoidance and symptoms of negative cognition, such as social estrangement or diminished interest in activities. Previous studies have demonstrated that single prolonged stress (SPS), models PTSD phenotypes, including impairments in learning and memory. Therefore, it was hypothesized that SPS would impair social and object recognition memory. Male Sprague Dawley rats were exposed to SPS then tested in the social choice test (SCT) or novel object recognition test (NOR). These tests measure recognition of novelty over familiarity, a natural preference of rodents. Results show that SPS impaired preference for both social and object novelty. In addition, SPS impairment in social recognition may be caused by impaired behavioral flexibility, or an inability to shift behavior during the SCT. These results demonstrate that traumatic stress can impair social and object recognition memory, which may underlie certain avoidant symptoms or negative cognition in PTSD and be related to impaired behavioral flexibility. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. DIAC object recognition system

    NASA Astrophysics Data System (ADS)

    Buurman, Johannes

    1992-03-01

    This paper describes the object recognition system used in an intelligent robot cell. It is used to recognize and estimate pose and orientation of parts as they enter the cell. The parts are mostly metal and consist of polyhedral and cylindrical shapes. The system uses feature-based stereo vision to acquire a wireframe of the observed part. Features are defined as straight lines and ellipses, which lead to a wireframe of straight lines and circular arcs (the latter using a new algorithm). This wireframe is compared to a number of wire frame models obtained from the CAD database. Experimental results show that image processing hardware and parallelization may add considerably to the speed of the system.

  1. Object recognition of ladar with support vector machine

    NASA Astrophysics Data System (ADS)

    Sun, Jian-Feng; Li, Qi; Wang, Qi

    2005-01-01

    Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

  2. Object Recognition and Localization: The Role of Tactile Sensors

    PubMed Central

    Aggarwal, Achint; Kirchner, Frank

    2014-01-01

    Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments. PMID:24553087

  3. Automatic image database generation from CAD for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Sardana, Harish K.; Daemi, Mohammad F.; Ibrahim, Mohammad K.

    1993-06-01

    The development and evaluation of Multiple-View 3-D object recognition systems is based on a large set of model images. Due to the various advantages of using CAD, it is becoming more and more practical to use existing CAD data in computer vision systems. Current PC- level CAD systems are capable of providing physical image modelling and rendering involving positional variations in cameras, light sources etc. We have formulated a modular scheme for automatic generation of various aspects (views) of the objects in a model based 3-D object recognition system. These views are generated at desired orientations on the unit Gaussian sphere. With a suitable network file sharing system (NFS), the images can directly be stored on a database located on a file server. This paper presents the image modelling solutions using CAD in relation to multiple-view approach. Our modular scheme for data conversion and automatic image database storage for such a system is discussed. We have used this approach in 3-D polyhedron recognition. An overview of the results, advantages and limitations of using CAD data and conclusions using such as scheme are also presented.

  4. Affective and contextual values modulate spatial frequency use in object recognition

    PubMed Central

    Caplette, Laurent; West, Gregory; Gomot, Marie; Gosselin, Frédéric; Wicker, Bruno

    2014-01-01

    Visual object recognition is of fundamental importance in our everyday interaction with the environment. Recent models of visual perception emphasize the role of top-down predictions facilitating object recognition via initial guesses that limit the number of object representations that need to be considered. Several results suggest that this rapid and efficient object processing relies on the early extraction and processing of low spatial frequencies (LSF). The present study aimed to investigate the SF content of visual object representations and its modulation by contextual and affective values of the perceived object during a picture-name verification task. Stimuli consisted of pictures of objects equalized in SF content and categorized as having low or high affective and contextual values. To access the SF content of stored visual representations of objects, SFs of each image were then randomly sampled on a trial-by-trial basis. Results reveal that intermediate SFs between 14 and 24 cycles per object (2.3–4 cycles per degree) are correlated with fast and accurate identification for all categories of objects. Moreover, there was a significant interaction between affective and contextual values over the SFs correlating with fast recognition. These results suggest that affective and contextual values of a visual object modulate the SF content of its internal representation, thus highlighting the flexibility of the visual recognition system. PMID:24904514

  5. A cortical framework for invariant object categorization and recognition.

    PubMed

    Rodrigues, João; Hans du Buf, J M

    2009-08-01

    In this paper we present a new model for invariant object categorization and recognition. It is based on explicit multi-scale features: lines, edges and keypoints are extracted from responses of simple, complex and end-stopped cells in cortical area V1, and keypoints are used to construct saliency maps for Focus-of-Attention. The model is a functional but dichotomous one, because keypoints are employed to model the "where" data stream, with dynamic routing of features from V1 to higher areas to obtain translation, rotation and size invariance, whereas lines and edges are employed in the "what" stream for object categorization and recognition. Furthermore, both the "where" and "what" pathways are dynamic in that information at coarse scales is employed first, after which information at progressively finer scales is added in order to refine the processes, i.e., both the dynamic feature routing and the categorization level. The construction of group and object templates, which are thought to be available in the prefrontal cortex with "what" and "where" components in PF46d and PF46v, is also illustrated. The model was tested in the framework of an integrated and biologically plausible architecture.

  6. Lateral Entorhinal Cortex is Critical for Novel Object-Context Recognition

    PubMed Central

    Wilson, David IG; Langston, Rosamund F; Schlesiger, Magdalene I; Wagner, Monica; Watanabe, Sakurako; Ainge, James A

    2013-01-01

    Episodic memory incorporates information about specific events or occasions including spatial locations and the contextual features of the environment in which the event took place. It has been modeled in rats using spontaneous exploration of novel configurations of objects, their locations, and the contexts in which they are presented. While we have a detailed understanding of how spatial location is processed in the brain relatively little is known about where the nonspatial contextual components of episodic memory are processed. Initial experiments measured c-fos expression during an object-context recognition (OCR) task to examine which networks within the brain process contextual features of an event. Increased c-fos expression was found in the lateral entorhinal cortex (LEC; a major hippocampal afferent) during OCR relative to control conditions. In a subsequent experiment it was demonstrated that rats with lesions of LEC were unable to recognize object-context associations yet showed normal object recognition and normal context recognition. These data suggest that contextual features of the environment are integrated with object identity in LEC and demonstrate that recognition of such object-context associations requires the LEC. This is consistent with the suggestion that contextual features of an event are processed in LEC and that this information is combined with spatial information from medial entorhinal cortex to form episodic memory in the hippocampus. © 2013 Wiley Periodicals, Inc. PMID:23389958

  7. Nicotine Administration Attenuates Methamphetamine-Induced Novel Object Recognition Deficits

    PubMed Central

    Vieira-Brock, Paula L.; McFadden, Lisa M.; Nielsen, Shannon M.; Smith, Misty D.; Hanson, Glen R.

    2015-01-01

    Background: Previous studies have demonstrated that methamphetamine abuse leads to memory deficits and these are associated with relapse. Furthermore, extensive evidence indicates that nicotine prevents and/or improves memory deficits in different models of cognitive dysfunction and these nicotinic effects might be mediated by hippocampal or cortical nicotinic acetylcholine receptors. The present study investigated whether nicotine attenuates methamphetamine-induced novel object recognition deficits in rats and explored potential underlying mechanisms. Methods: Adolescent or adult male Sprague-Dawley rats received either nicotine water (10–75 μg/mL) or tap water for several weeks. Methamphetamine (4×7.5mg/kg/injection) or saline was administered either before or after chronic nicotine exposure. Novel object recognition was evaluated 6 days after methamphetamine or saline. Serotonin transporter function and density and α4β2 nicotinic acetylcholine receptor density were assessed on the following day. Results: Chronic nicotine intake via drinking water beginning during either adolescence or adulthood attenuated the novel object recognition deficits caused by a high-dose methamphetamine administration. Similarly, nicotine attenuated methamphetamine-induced deficits in novel object recognition when administered after methamphetamine treatment. However, nicotine did not attenuate the serotonergic deficits caused by methamphetamine in adults. Conversely, nicotine attenuated methamphetamine-induced deficits in α4β2 nicotinic acetylcholine receptor density in the hippocampal CA1 region. Furthermore, nicotine increased α4β2 nicotinic acetylcholine receptor density in the hippocampal CA3, dentate gyrus and perirhinal cortex in both saline- and methamphetamine-treated rats. Conclusions: Overall, these findings suggest that nicotine-induced increases in α4β2 nicotinic acetylcholine receptors in the hippocampus and perirhinal cortex might be one mechanism by which

  8. Detailed 3D representations for object recognition and modeling.

    PubMed

    Zia, M Zeeshan; Stark, Michael; Schiele, Bernt; Schindler, Konrad

    2013-11-01

    Geometric 3D reasoning at the level of objects has received renewed attention recently in the context of visual scene understanding. The level of geometric detail, however, is typically limited to qualitative representations or coarse boxes. This is linked to the fact that today's object class detectors are tuned toward robust 2D matching rather than accurate 3D geometry, encouraged by bounding-box-based benchmarks such as Pascal VOC. In this paper, we revisit ideas from the early days of computer vision, namely, detailed, 3D geometric object class representations for recognition. These representations can recover geometrically far more accurate object hypotheses than just bounding boxes, including continuous estimates of object pose and 3D wireframes with relative 3D positions of object parts. In combination with robust techniques for shape description and inference, we outperform state-of-the-art results in monocular 3D pose estimation. In a series of experiments, we analyze our approach in detail and demonstrate novel applications enabled by such an object class representation, such as fine-grained categorization of cars and bicycles, according to their 3D geometry, and ultrawide baseline matching.

  9. Hierarchical Context Modeling for Video Event Recognition.

    PubMed

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

    Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

  10. Breaking object correspondence across saccades impairs object recognition: The role of color and luminance.

    PubMed

    Poth, Christian H; Schneider, Werner X

    2016-09-01

    Rapid saccadic eye movements bring the foveal region of the eye's retina onto objects for high-acuity vision. Saccades change the location and resolution of objects' retinal images. To perceive objects as visually stable across saccades, correspondence between the objects before and after the saccade must be established. We have previously shown that breaking object correspondence across the saccade causes a decrement in object recognition (Poth, Herwig, & Schneider, 2015). Color and luminance can establish object correspondence, but it is unknown how these surface features contribute to transsaccadic visual processing. Here, we investigated whether changing the surface features color-and-luminance and color alone across saccades impairs postsaccadic object recognition. Participants made saccades to peripheral objects, which either maintained or changed their surface features across the saccade. After the saccade, participants briefly viewed a letter within the saccade target object (terminated by a pattern mask). Postsaccadic object recognition was assessed as participants' accuracy in reporting the letter. Experiment A used the colors green and red with different luminances as surface features, Experiment B blue and yellow with approximately the same luminances. Changing the surface features across the saccade deteriorated postsaccadic object recognition in both experiments. These findings reveal a link between object recognition and object correspondence relying on the surface features colors and luminance, which is currently not addressed in theories of transsaccadic perception. We interpret the findings within a recent theory ascribing this link to visual attention (Schneider, 2013).

  11. Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

    PubMed

    Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

    2017-07-01

    According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

  12. Examining object recognition and object-in-Place memory in plateau zokors, Eospalax baileyi.

    PubMed

    Hegab, Ibrahim M; Tan, Yuchen; Wang, Chan; Yao, Baohui; Wang, Haifang; Ji, Weihong; Su, Junhu

    2018-01-01

    Recognition memory is important for the survival and fitness of subterranean rodents due to the barren underground conditions that require avoiding the burden of higher energy costs or possible conflict with conspecifics. Our study aims to examine the object and object/place recognition memories in plateau zokors (Eospalax baileyi) and test whether their underground life exerts sex-specific differences in memory functions using Novel Object Recognition (NOR) and Object-in-Place (OiP) paradigms. Animals were tested in the NOR with short (10min) and long-term (24h) inter-trial intervals (ITI) and in the OiP for a 30-min ITI between the familiarization and testing sessions. Plateau zokors showed a strong preference for novel objects manifested by a longer exploration time for the novel object after 10min ITI but failed to remember the familiar object when tested after 24h, suggesting a lack of long-term memory. In the OiP test, zokors effectively formed an association between the objects and the place where they were formerly encountered, resulting in a higher duration of exploration to the switched objects. However, both sexes showed equivalent results in exploration time during the NOR and OiP tests, which eliminates the possibility of discovering sex-specific variations in memory performance. Taken together, our study illustrates robust novelty preference and an effective short-term recognition memory without marked sex-specific differences, which might elucidate the dynamics of recognition memory formation and retrieval in plateau zokors. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Image Processing Strategies Based on a Visual Saliency Model for Object Recognition Under Simulated Prosthetic Vision.

    PubMed

    Wang, Jing; Li, Heng; Fu, Weizhen; Chen, Yao; Li, Liming; Lyu, Qing; Han, Tingting; Chai, Xinyu

    2016-01-01

    Retinal prostheses have the potential to restore partial vision. Object recognition in scenes of daily life is one of the essential tasks for implant wearers. Still limited by the low-resolution visual percepts provided by retinal prostheses, it is important to investigate and apply image processing methods to convey more useful visual information to the wearers. We proposed two image processing strategies based on Itti's visual saliency map, region of interest (ROI) extraction, and image segmentation. Itti's saliency model generated a saliency map from the original image, in which salient regions were grouped into ROI by the fuzzy c-means clustering. Then Grabcut generated a proto-object from the ROI labeled image which was recombined with background and enhanced in two ways--8-4 separated pixelization (8-4 SP) and background edge extraction (BEE). Results showed that both 8-4 SP and BEE had significantly higher recognition accuracy in comparison with direct pixelization (DP). Each saliency-based image processing strategy was subject to the performance of image segmentation. Under good and perfect segmentation conditions, BEE and 8-4 SP obtained noticeably higher recognition accuracy than DP, and under bad segmentation condition, only BEE boosted the performance. The application of saliency-based image processing strategies was verified to be beneficial to object recognition in daily scenes under simulated prosthetic vision. They are hoped to help the development of the image processing module for future retinal prostheses, and thus provide more benefit for the patients. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  14. Development of a sonar-based object recognition system

    NASA Astrophysics Data System (ADS)

    Ecemis, Mustafa Ihsan

    2001-02-01

    Sonars are used extensively in mobile robotics for obstacle detection, ranging and avoidance. However, these range-finding applications do not exploit the full range of information carried in sonar echoes. In addition, mobile robots need robust object recognition systems. Therefore, a simple and robust object recognition system using ultrasonic sensors may have a wide range of applications in robotics. This dissertation develops and analyzes an object recognition system that uses ultrasonic sensors of the type commonly found on mobile robots. Three principal experiments are used to test the sonar recognition system: object recognition at various distances, object recognition during unconstrained motion, and softness discrimination. The hardware setup, consisting of an inexpensive Polaroid sonar and a data acquisition board, is described first. The software for ultrasound signal generation, echo detection, data collection, and data processing is then presented. Next, the dissertation describes two methods to extract information from the echoes, one in the frequency domain and the other in the time domain. The system uses the fuzzy ARTMAP neural network to recognize objects on the basis of the information content of their echoes. In order to demonstrate that the performance of the system does not depend on the specific classification method being used, the K- Nearest Neighbors (KNN) Algorithm is also implemented. KNN yields a test accuracy similar to fuzzy ARTMAP in all experiments. Finally, the dissertation describes a method for extracting features from the envelope function in order to reduce the dimension of the input vector used by the classifiers. Decreasing the size of the input vectors reduces the memory requirements of the system and makes it run faster. It is shown that this method does not affect the performance of the system dramatically and is more appropriate for some tasks. The results of these experiments demonstrate that sonar can be used to develop

  15. Running Improves Pattern Separation during Novel Object Recognition.

    PubMed

    Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

    2015-10-09

    Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

  16. Neurocomputational bases of object and face recognition.

    PubMed Central

    Biederman, I; Kalocsai, P

    1997-01-01

    A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in a two-dimensional (2D) coordinate space, as proposed by C. von der Malsburg and his associates, may account for many of the phenomena associated with face recognition. An additional refinement, in which each column of filters (termed a 'jet') is centred on a particular facial feature (or fiducial point), allows selectivity of the input into the holistic representation to avoid incorporation of occluding or nearby surfaces. The initial hypercolumn representation also characterizes the first stage of object perception, but the image variation for objects at a given location in a 2D coordinate space may be too great to yield sufficient predictability directly from the output of spatial kernels. Consequently, objects can be represented by a structural description specifying qualitative (typically, non-accidental) characterizations of an object's parts, the attributes of the parts, and the relations among the parts, largely based on orientation and depth discontinuities (as shown by Hummel & Biederman). A series of experiments on the name priming or physical matching of complementary images (in the Fourier domain) of objects and faces documents that whereas face recognition is strongly dependent on the original spatial filter values, evidence from object recognition indicates strong invariance to these values, even when distinguishing among objects that are as similar as faces. PMID:9304687

  17. How does the brain solve visual object recognition?

    PubMed Central

    Zoccolan, Davide; Rust, Nicole C.

    2012-01-01

    Mounting evidence suggests that “core object recognition,” the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive, largely feedforward computations that culminate in a powerful neuronal representation in the inferior temporal cortex. However, the algorithm that produces this solution remains little-understood. Here we review evidence ranging from individual neurons, to neuronal populations, to behavior, to computational models. We propose that understanding this algorithm will require using neuronal and psychophysical data to sift through many computational models, each based on building blocks of small, canonical sub-networks with a common functional goal. PMID:22325196

  18. Three Dimensional Object Recognition Using an Unsupervised Neural Network: Understanding the Distinguishing Features

    DTIC Science & Technology

    1992-12-23

    predominance of structural models of recognition, of which a recent example is the Recognition By Components (RBC) theory ( Biederman , 1987 ). Structural...related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived from a biologically motivated computational theory (Bienenstock et...dimensional object recognition (Intrator and Gold, 1991). The method is related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived

  19. Size-Sensitive Perceptual Representations Underlie Visual and Haptic Object Recognition

    PubMed Central

    Craddock, Matt; Lawson, Rebecca

    2009-01-01

    A variety of similarities between visual and haptic object recognition suggests that the two modalities may share common representations. However, it is unclear whether such common representations preserve low-level perceptual features or whether transfer between vision and haptics is mediated by high-level, abstract representations. Two experiments used a sequential shape-matching task to examine the effects of size changes on unimodal and crossmodal visual and haptic object recognition. Participants felt or saw 3D plastic models of familiar objects. The two objects presented on a trial were either the same size or different sizes and were the same shape or different but similar shapes. Participants were told to ignore size changes and to match on shape alone. In Experiment 1, size changes on same-shape trials impaired performance similarly for both visual-to-visual and haptic-to-haptic shape matching. In Experiment 2, size changes impaired performance on both visual-to-haptic and haptic-to-visual shape matching and there was no interaction between the cost of size changes and direction of transfer. Together the unimodal and crossmodal matching results suggest that the same, size-specific perceptual representations underlie both visual and haptic object recognition, and indicate that crossmodal memory for objects must be at least partly based on common perceptual representations. PMID:19956685

  20. Priming Contour-Deleted Images: Evidence for Immediate Representations in Visual Object Recognition.

    ERIC Educational Resources Information Center

    Biederman, Irving; Cooper, Eric E.

    1991-01-01

    Speed and accuracy of identification of pictures of objects are facilitated by prior viewing. Contributions of image features, convex or concave components, and object models in a repetition priming task were explored in 2 studies involving 96 college students. Results provide evidence of intermediate representations in visual object recognition.…

  1. DORSAL HIPPOCAMPAL PROGESTERONE INFUSIONS ENHANCE OBJECT RECOGNITION IN YOUNG FEMALE MICE

    PubMed Central

    Orr, Patrick T.; Lewis, Michael C.; Frick, Karyn M.

    2009-01-01

    The effects of progesterone on memory are not nearly as well studied as the effects of estrogens. Although progesterone can reportedly enhance spatial and/or object recognition in female rodents when given immediately after training, previous studies have injected progesterone systemically, and therefore, the brain regions mediating this enhancement are not clear. As such, this study was designed to determine the role of the dorsal hippocampus in mediating the beneficial effect of progesterone on object recognition. Young ovariectomized C57BL/6 mice were trained in a hippocampal-dependent object recognition task utilizing two identical objects, and then immediately or 2 hrs afterwards, received bilateral dorsal hippocampal infusions of vehicle or 0.01, 0.1, or 1.0 μg/μl water-soluble progesterone. Forty-eight hours later, object recognition memory was tested using a previously explored object and a novel object. Relative to the vehicle group, memory for the familiar object was enhanced in all groups receiving immediate infusions of progesterone. Progesterone infusion delayed 2 hrs after training did not affect object recognition. These data suggest that the dorsal hippocampus may play a critical role in progesterone-induced enhancement of object recognition. PMID:19477194

  2. Object Recognition using Feature- and Color-Based Methods

    NASA Technical Reports Server (NTRS)

    Duong, Tuan; Duong, Vu; Stubberud, Allen

    2008-01-01

    An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

  3. Experience moderates overlap between object and face recognition, suggesting a common ability

    PubMed Central

    Gauthier, Isabel; McGugin, Rankin W.; Richler, Jennifer J.; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E.

    2014-01-01

    Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. PMID:24993021

  4. Experience moderates overlap between object and face recognition, suggesting a common ability.

    PubMed

    Gauthier, Isabel; McGugin, Rankin W; Richler, Jennifer J; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E

    2014-07-03

    Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. © 2014 ARVO.

  5. Decreased acetylcholine release delays the consolidation of object recognition memory.

    PubMed

    De Jaeger, Xavier; Cammarota, Martín; Prado, Marco A M; Izquierdo, Iván; Prado, Vania F; Pereira, Grace S

    2013-02-01

    Acetylcholine (ACh) is important for different cognitive functions such as learning, memory and attention. The release of ACh depends on its vesicular loading by the vesicular acetylcholine transporter (VAChT). It has been demonstrated that VAChT expression can modulate object recognition memory. However, the role of VAChT expression on object recognition memory persistence still remains to be understood. To address this question we used distinct mouse lines with reduced expression of VAChT, as well as pharmacological manipulations of the cholinergic system. We showed that reduction of cholinergic tone impairs object recognition memory measured at 24h. Surprisingly, object recognition memory, measured at 4 days after training, was impaired by substantial, but not moderate, reduction in VAChT expression. Our results suggest that levels of acetylcholine release strongly modulate object recognition memory consolidation and appear to be of particular importance for memory persistence 4 days after training. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    PubMed

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  7. A method of object recognition for single pixel imaging

    NASA Astrophysics Data System (ADS)

    Li, Boxuan; Zhang, Wenwen

    2018-01-01

    Computational ghost imaging(CGI), utilizing a single-pixel detector, has been extensively used in many fields. However, in order to achieve a high-quality reconstructed image, a large number of iterations are needed, which limits the flexibility of using CGI in practical situations, especially in the field of object recognition. In this paper, we purpose a method utilizing the feature matching to identify the number objects. In the given system, approximately 90% of accuracy of recognition rates can be achieved, which provides a new idea for the application of single pixel imaging in the field of object recognition

  8. Object Recognition Memory and the Rodent Hippocampus

    ERIC Educational Resources Information Center

    Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

    2010-01-01

    In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

  9. A Taxonomy of 3D Occluded Objects Recognition Techniques

    NASA Astrophysics Data System (ADS)

    Soleimanizadeh, Shiva; Mohamad, Dzulkifli; Saba, Tanzila; Al-ghamdi, Jarallah Saleh

    2016-03-01

    The overall performances of object recognition techniques under different condition (e.g., occlusion, viewpoint, and illumination) have been improved significantly in recent years. New applications and hardware are shifted towards digital photography, and digital media. This faces an increase in Internet usage requiring object recognition for certain applications; particularly occulded objects. However occlusion is still an issue unhandled, interlacing the relations between extracted feature points through image, research is going on to develop efficient techniques and easy to use algorithms that would help users to source images; this need to overcome problems and issues regarding occlusion. The aim of this research is to review recognition occluded objects algorithms and figure out their pros and cons to solve the occlusion problem features, which are extracted from occluded object to distinguish objects from other co-existing objects by determining the new techniques, which could differentiate the occluded fragment and sections inside an image.

  10. Data-driven indexing mechanism for the recognition of polyhedral objects

    NASA Astrophysics Data System (ADS)

    McLean, Stewart; Horan, Peter; Caelli, Terry M.

    1992-02-01

    This paper is concerned with the problem of searching large model databases. To date, most object recognition systems have concentrated on the problem of matching using simple searching algorithms. This is quite acceptable when the number of object models is small. However, in the future, general purpose computer vision systems will be required to recognize hundreds or perhaps thousands of objects and, in such circumstances, efficient searching algorithms will be needed. The problem of searching a large model database is one which must be addressed if future computer vision systems are to be at all effective. In this paper we present a method we call data-driven feature-indexed hypothesis generation as one solution to the problem of searching large model databases.

  11. Examining Object Location and Object Recognition Memory in Mice

    PubMed Central

    Vogel-Ciernia, Annie; Wood, Marcelo A.

    2014-01-01

    Unit Introduction The ability to store and recall our life experiences defines a person's identity. Consequently, the loss of long-term memory is a particularly devastating part of a variety of cognitive disorders, diseases and injuries. There is a great need to develop therapeutics to treat memory disorders, and thus a variety of animal models and memory paradigms have been developed. Mouse models have been widely used both to study basic disease mechanisms and to evaluate potential drug targets for therapeutic development. The relative ease of genetic manipulation of Mus musculus has led to a wide variety of genetically altered mice that model cognitive disorders ranging from Alzheimer's disease to autism. Rodents, including mice, are particularly adept at encoding and remembering spatial relationships, and these long-term spatial memories are dependent on the medial temporal lobe of the brain. These brain regions are also some of the first and most heavily impacted in disorders of human memory including Alzheimer's disease. Consequently, some of the simplest and most commonly used tests of long-term memory in mice are those that examine memory for objects and spatial relationships. However, many of these tasks, such as Morris water maze and contextual fear conditioning, are dependent upon the encoding and retrieval of emotionally aversive and inherently stressful training events. While these types of memories are important, they do not reflect the typical day-to-day experiences or memories most commonly affected in human disease. In addition, stress hormone release alone can modulate memory and thus obscure or artificially enhance these types of tasks. To avoid these sorts of confounds, we and many others have utilized tasks testing animals’ memory for object location and novel object recognition. These tasks involve exploiting rodents’ innate preference for novelty, and are inherently not stressful. In this protocol we detail how memory for object location

  12. Behavioral model of visual perception and recognition

    NASA Astrophysics Data System (ADS)

    Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

    1993-09-01

    In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and

  13. Crowded and Sparse Domains in Object Recognition: Consequences for Categorization and Naming

    ERIC Educational Resources Information Center

    Gale, Tim M.; Laws, Keith R.; Foley, Kerry

    2006-01-01

    Some models of object recognition propose that items from structurally crowded categories (e.g., living things) permit faster access to superordinate semantic information than structurally dissimilar categories (e.g., nonliving things), but slower access to individual object information when naming items. We present four experiments that utilize…

  14. The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

    NASA Astrophysics Data System (ADS)

    Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

    2017-10-01

    This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

  15. Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats

    PubMed Central

    Rosselli, Federica B.; Alemi, Alireza; Ansuini, Alessio; Zoccolan, Davide

    2015-01-01

    In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning. PMID:25814936

  16. Three-dimensional object recognition using similar triangles and decision trees

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly

    1993-01-01

    A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.

  17. Metric invariance in object recognition: a review and further evidence.

    PubMed

    Cooper, E E; Biederman, I; Hummel, J E

    1992-06-01

    Phenomenologically, human shape recognition appears to be invariant with changes of orientation in depth (up to parts occlusion), position in the visual field, and size. Recent versions of template theories (e.g., Ullman, 1989; Lowe, 1987) assume that these invariances are achieved through the application of transformations such as rotation, translation, and scaling of the image so that it can be matched metrically to a stored template. Presumably, such transformations would require time for their execution. We describe recent priming experiments in which the effects of a prior brief presentation of an image on its subsequent recognition are assessed. The results of these experiments indicate that the invariance is complete: The magnitude of visual priming (as distinct from name or basic level concept priming) is not affected by a change in position, size, orientation in depth, or the particular lines and vertices present in the image, as long as representations of the same components can be activated. An implemented seven layer neural network model (Hummel & Biederman, 1992) that captures these fundamental properties of human object recognition is described. Given a line drawing of an object, the model activates a viewpoint-invariant structural description of the object, specifying its parts and their interrelations. Visual priming is interpreted as a change in the connection weights for the activation of: a) cells, termed geon feature assemblies (GFAs), that conjoin the output of units that represent invariant, independent properties of a single geon and its relations (such as its type, aspect ratio, relations to other geons), or b) a change in the connection weights by which several GFAs activate a cell representing an object.

  18. Modeling recall memory for emotional objects in Alzheimer's disease.

    PubMed

    Sundstrøm, Martin

    2011-07-01

    To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p < .003). EM was not found for recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p < .014) and object status (p < .0001) as gift or non-gift. Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

  19. Developmental Commonalities between Object and Face Recognition in Adolescence

    PubMed Central

    Jüttner, Martin; Wakui, Elley; Petters, Dean; Davidoff, Jules

    2016-01-01

    In the visual perception literature, the recognition of faces has often been contrasted with that of non-face objects, in terms of differences with regard to the role of parts, part relations and holistic processing. However, recent evidence from developmental studies has begun to blur this sharp distinction. We review evidence for a protracted development of object recognition that is reminiscent of the well-documented slow maturation observed for faces. The prolonged development manifests itself in a retarded processing of metric part relations as opposed to that of individual parts and offers surprising parallels to developmental accounts of face recognition, even though the interpretation of the data is less clear with regard to holistic processing. We conclude that such results might indicate functional commonalities between the mechanisms underlying the recognition of faces and non-face objects, which are modulated by different task requirements in the two stimulus domains. PMID:27014176

  20. An ERP Study on Self-Relevant Object Recognition

    ERIC Educational Resources Information Center

    Miyakoshi, Makoto; Nomura, Michio; Ohira, Hideki

    2007-01-01

    We performed an event-related potential study to investigate the self-relevance effect in object recognition. Three stimulus categories were prepared: SELF (participant's own objects), FAMILIAR (disposable and public objects, defined as objects with less-self-relevant familiarity), and UNFAMILIAR (others' objects). The participants' task was to…

  1. The development of newborn object recognition in fast and slow visual worlds

    PubMed Central

    Wood, Justin N.; Wood, Samantha M. W.

    2016-01-01

    Object recognition is central to perception and cognition. Yet relatively little is known about the environmental factors that cause invariant object recognition to emerge in the newborn brain. Is this ability a hardwired property of vision? Or does the development of invariant object recognition require experience with a particular kind of visual environment? Here, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) require visual experience with slowly changing objects to develop invariant object recognition abilities. When newborn chicks were raised with a slowly rotating virtual object, the chicks built invariant object representations that generalized across novel viewpoints and rotation speeds. In contrast, when newborn chicks were raised with a virtual object that rotated more quickly, the chicks built viewpoint-specific object representations that failed to generalize to novel viewpoints and rotation speeds. Moreover, there was a direct relationship between the speed of the object and the amount of invariance in the chick's object representation. Thus, visual experience with slowly changing objects plays a critical role in the development of invariant object recognition. These results indicate that invariant object recognition is not a hardwired property of vision, but is learned rapidly when newborns encounter a slowly changing visual world. PMID:27097925

  2. Fast and efficient indexing approach for object recognition

    NASA Astrophysics Data System (ADS)

    Hefnawy, Alaa; Mashali, Samia A.; Rashwan, Mohsen; Fikri, Magdi

    1999-08-01

    This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

  3. Model-based occluded object recognition using Petri nets

    NASA Astrophysics Data System (ADS)

    Zhou, Chuan; Hura, Gurdeep S.

    1998-09-01

    This paper discusses the use of Petri nets to model the process of the object matching between an image and a model under different 2D geometric transformations. This transformation finds its applications in sensor-based robot control, flexible manufacturing system and industrial inspection, etc. A description approach for object structure is presented by its topological structure relation called Point-Line Relation Structure (PLRS). It has been shown how Petri nets can be used to model the matching process, and an optimal or near optimal matching can be obtained by tracking the reachability graph of the net. The experiment result shows that object can be successfully identified and located under 2D transformation such as translations, rotations, scale changes and distortions due to object occluded partially.

  4. Multi-objects recognition for distributed intelligent sensor networks

    NASA Astrophysics Data System (ADS)

    He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

    2008-04-01

    This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

  5. Feedforward object-vision models only tolerate small image variations compared to human

    PubMed Central

    Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

    2014-01-01

    Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986

  6. The evolution of meaning: spatio-temporal dynamics of visual object recognition.

    PubMed

    Clarke, Alex; Taylor, Kirsten I; Tyler, Lorraine K

    2011-08-01

    Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity is driven by increasing semantic integration demands as defined by the complexity of semantic information required by the task and driven by the stimuli. To test this prediction, we recorded magnetoencephalography data while participants named living and nonliving objects during two naming tasks. We found that the spatio-temporal dynamics of neural activity were modulated by the level of semantic integration required. Specifically, source reconstructed time courses and phase synchronization measures showed increased recurrent interactions as a function of semantic integration demands. These findings demonstrate that the cortical dynamics of object processing are modulated by the complexity of semantic information required from the visual input.

  7. Object, spatial and social recognition testing in a single test paradigm.

    PubMed

    Lian, Bin; Gao, Jun; Sui, Nan; Feng, Tingyong; Li, Ming

    2018-07-01

    Animals have the ability to process information about an object or a conspecific's physical features and location, and alter its behavior when such information is updated. In the laboratory, the object, spatial and social recognition are often studied in separate tasks, making them unsuitable to study the potential dissociations and interactions among various types of recognition memories. The present study introduced a single paradigm to detect the object and spatial recognition, and social recognition of a familiar and novel conspecific. Specifically, male and female Sprague-Dawley adult (>75 days old) or preadolescent (25-28 days old) rats were tested with two objects and one social partner in an open-field arena for four 10-min sessions with a 20-min inter-session interval. After the first sample session, a new object replaced one of the sampled objects in the second session, and the location of one of the old objects was changed in the third session. Finally, a new social partner was introduced in the fourth session and replaced the familiar one. Exploration time with each stimulus was recorded and measures for the three recognitions were calculated based on the discrimination ratio. Overall results show that adult and preadolescent male and female rats spent more time exploring the social partner than the objects, showing a clear preference for social stimulus over nonsocial one. They also did not differ in their abilities to discriminate a new object, a new location and a new social partner from a familiar one, and to recognize a familiar conspecific. Acute administration of MK-801 (a NMDA receptor antagonist, 0.025 and 0.10 mg/kg, i.p.) after the sample session dose-dependently reduced the total time spent on exploring the social partner and objects in the adult rats, and had a significantly larger effect in the females than in the males. MK-801 also dose-dependently increased motor activity. However, it did not alter the object, spatial and social

  8. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

    PubMed Central

    Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

    2015-01-01

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  9. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  10. Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision.

    PubMed

    Li, Heng; Su, Xiaofan; Wang, Jing; Kan, Han; Han, Tingting; Zeng, Yajie; Chai, Xinyu

    2018-01-01

    Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual perception, prosthetic recipients can just complete some simple visual tasks, but more complex tasks like face identification/object recognition are extremely difficult. Therefore, it is necessary to investigate and apply image processing strategies for optimizing the visual perception of the recipients. This study focuses on recognition of the object of interest employing simulated prosthetic vision. We used a saliency segmentation method based on a biologically plausible graph-based visual saliency model and a grabCut-based self-adaptive-iterative optimization framework to automatically extract foreground objects. Based on this, two image processing strategies, Addition of Separate Pixelization and Background Pixel Shrink, were further utilized to enhance the extracted foreground objects. i) The results showed by verification of psychophysical experiments that under simulated prosthetic vision, both strategies had marked advantages over Direct Pixelization in terms of recognition accuracy and efficiency. ii) We also found that recognition performance under two strategies was tied to the segmentation results and was affected positively by the paired-interrelated objects in the scene. The use of the saliency segmentation method and image processing strategies can automatically extract and enhance foreground objects, and significantly improve object recognition performance towards recipients implanted a high-density implant. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Invariant visual object recognition: a model, with lighting invariance.

    PubMed

    Rolls, Edmund T; Stringer, Simon M

    2006-01-01

    How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.

  12. It Takes Two–Skilled Recognition of Objects Engages Lateral Areas in Both Hemispheres

    PubMed Central

    Bilalić, Merim; Kiesel, Andrea; Pohl, Carsten; Erb, Michael; Grodd, Wolfgang

    2011-01-01

    Our object recognition abilities, a direct product of our experience with objects, are fine-tuned to perfection. Left temporal and lateral areas along the dorsal, action related stream, as well as left infero-temporal areas along the ventral, object related stream are engaged in object recognition. Here we show that expertise modulates the activity of dorsal areas in the recognition of man-made objects with clearly specified functions. Expert chess players were faster than chess novices in identifying chess objects and their functional relations. Experts' advantage was domain-specific as there were no differences between groups in a control task featuring geometrical shapes. The pattern of eye movements supported the notion that experts' extensive knowledge about domain objects and their functions enabled superior recognition even when experts were not directly fixating the objects of interest. Functional magnetic resonance imaging (fMRI) related exclusively the areas along the dorsal stream to chess specific object recognition. Besides the commonly involved left temporal and parietal lateral brain areas, we found that only in experts homologous areas on the right hemisphere were also engaged in chess specific object recognition. Based on these results, we discuss whether skilled object recognition does not only involve a more efficient version of the processes found in non-skilled recognition, but also qualitatively different cognitive processes which engage additional brain areas. PMID:21283683

  13. Measuring the Speed of Newborn Object Recognition in Controlled Visual Worlds

    ERIC Educational Resources Information Center

    Wood, Justin N.; Wood, Samantha M. W.

    2017-01-01

    How long does it take for a newborn to recognize an object? Adults can recognize objects rapidly, but measuring object recognition speed in newborns has not previously been possible. Here we introduce an automated controlled-rearing method for measuring the speed of newborn object recognition in controlled visual worlds. We raised newborn chicks…

  14. Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly; Reid, Max B.

    1994-01-01

    A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

  15. View-Based Models of 3D Object Recognition and Class-Specific Invariance

    DTIC Science & Technology

    1994-04-01

    underlie recognition of geon-like com- ponents (see Edelman, 1991 and Biederman , 1987 ). I(X -_ ta)II1y = (X - ta)TWTW(x -_ ta) (3) View-invariant features...Institute of Technology, 1993. neocortex. Biological Cybernetics, 1992. 14] I. Biederman . Recognition by components: a theory [20] B. Olshausen, C...Anderson, and D. Van Essen. A of human image understanding. Psychol. Review, neural model of visual attention and invariant pat- 94:115-147, 1987 . tern

  16. 3-D Object Recognition from Point Cloud Data

    NASA Astrophysics Data System (ADS)

    Smith, W.; Walker, A. S.; Zhang, B.

    2011-09-01

    The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs). Massively parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM) and digital elevation model (DEM), so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex roofs. Several case

  17. Ultra-fast Object Recognition from Few Spikes

    DTIC Science & Technology

    2005-07-06

    Computer Science and Artificial Intelligence Laboratory Ultra-fast Object Recognition from Few Spikes Chou Hung, Gabriel Kreiman , Tomaso Poggio...neural code for different kinds of object-related information. *The authors, Chou Hung and Gabriel Kreiman , contributed equally to this work...Supplementary Material is available at http://ramonycajal.mit.edu/ kreiman /resources/ultrafast

  18. Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

    PubMed Central

    Cadieu, Charles F.; Hong, Ha; Yamins, Daniel L. K.; Pinto, Nicolas; Ardila, Diego; Solomon, Ethan A.; Majaj, Najib J.; DiCarlo, James J.

    2014-01-01

    The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of “kernel analysis” that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds. PMID:25521294

  19. Extraction of edge-based and region-based features for object recognition

    NASA Astrophysics Data System (ADS)

    Coutts, Benjamin; Ravi, Srinivas; Hu, Gongzhu; Shrikhande, Neelima

    1993-08-01

    One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

  20. Exogenous temporal cues enhance recognition memory in an object-based manner.

    PubMed

    Ohyama, Junji; Watanabe, Katsumi

    2010-11-01

    Exogenous attention enhances the perception of attended items in both a space-based and an object-based manner. Exogenous attention also improves recognition memory for attended items in the space-based mode. However, it has not been examined whether object-based exogenous attention enhances recognition memory. To address this issue, we examined whether a sudden visual change in a task-irrelevant stimulus (an exogenous cue) would affect participants' recognition memory for items that were serially presented around a cued time. The results showed that recognition accuracy for an item was strongly enhanced when the visual cue occurred at the same location and time as the item (Experiments 1 and 2). The memory enhancement effect occurred when the exogenous visual cue and an item belonged to the same object (Experiments 3 and 4) and even when the cue was counterpredictive of the timing of an item to be asked about (Experiment 5). The present study suggests that an exogenous temporal cue automatically enhances the recognition accuracy for an item that is presented at close temporal proximity to the cue and that recognition memory enhancement occurs in an object-based manner.

  1. Method of synthesized phase objects for pattern recognition with rotation invariance

    NASA Astrophysics Data System (ADS)

    Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

    2015-11-01

    We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.

  2. Differential effects of spaced vs. massed training in long-term object-identity and object-location recognition memory.

    PubMed

    Bello-Medina, Paola C; Sánchez-Carrasco, Livia; González-Ornelas, Nadia R; Jeffery, Kathryn J; Ramírez-Amaya, Víctor

    2013-08-01

    Here we tested whether the well-known superiority of spaced training over massed training is equally evident in both object identity and object location recognition memory. We trained animals with objects placed in a variable or in a fixed location to produce a location-independent object identity memory or a location-dependent object representation. The training consisted of 5 trials that occurred either on one day (Massed) or over the course of 5 consecutive days (Spaced). The memory test was done in independent groups of animals either 24h or 7 days after the last training trial. In each test the animals were exposed to either a novel object, when trained with the objects in variable locations, or to a familiar object in a novel location, when trained with objects in fixed locations. The difference in time spent exploring the changed versus the familiar objects was used as a measure of recognition memory. For the object-identity-trained animals, spaced training produced clear evidence of recognition memory after both 24h and 7 days, but massed-training animals showed it only after 24h. In contrast, for the object-location-trained animals, recognition memory was evident after both retention intervals and with both training procedures. When objects were placed in variable locations for the two types of training and the test was done with a brand-new location, only the spaced-training animals showed recognition at 24h, but surprisingly, after 7 days, animals trained using both procedures were able to recognize the change, suggesting a post-training consolidation process. We suggest that the two training procedures trigger different neural mechanisms that may differ in the two segregated streams that process object information and that may consolidate differently. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Incrementally learning objects by touch: online discriminative and generative models for tactile-based recognition.

    PubMed

    Soh, Harold; Demiris, Yiannis

    2014-01-01

    Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the sparse online infinite Echo-State Gaussian process (OIESGP), we propose and compare two novel discriminative and generative tactile learners that produce probability distributions over objects during object grasping/palpation. To enable iterative improvement, our online methods incorporate training samples as they become available. We also describe incremental unsupervised learning mechanisms, based on novelty scores and extreme value theory, when teacher labels are not available. We present experimental results for both supervised and unsupervised learning tasks using the iCub humanoid, with tactile sensors on its five-fingered anthropomorphic hand, and 10 different object classes. Our classifiers perform comparably to state-of-the-art methods (C4.5 and SVM classifiers) and findings indicate that tactile signals are highly relevant for making accurate object classifications. We also show that accurate "early" classifications are possible using only 20-30 percent of the grasp sequence. For unsupervised learning, our methods generate high quality clusterings relative to the widely-used sequential k-means and self-organising map (SOM), and we present analyses into the differences between the approaches.

  4. Contributions of Low and High Spatial Frequency Processing to Impaired Object Recognition Circuitry in Schizophrenia

    PubMed Central

    Calderone, Daniel J.; Hoptman, Matthew J.; Martínez, Antígona; Nair-Collins, Sangeeta; Mauro, Cristina J.; Bar, Moshe; Javitt, Daniel C.; Butler, Pamela D.

    2013-01-01

    Patients with schizophrenia exhibit cognitive and sensory impairment, and object recognition deficits have been linked to sensory deficits. The “frame and fill” model of object recognition posits that low spatial frequency (LSF) information rapidly reaches the prefrontal cortex (PFC) and creates a general shape of an object that feeds back to the ventral temporal cortex to assist object recognition. Visual dysfunction findings in schizophrenia suggest a preferential loss of LSF information. This study used functional magnetic resonance imaging (fMRI) and resting state functional connectivity (RSFC) to investigate the contribution of visual deficits to impaired object “framing” circuitry in schizophrenia. Participants were shown object stimuli that were intact or contained only LSF or high spatial frequency (HSF) information. For controls, fMRI revealed preferential activation to LSF information in precuneus, superior temporal, and medial and dorsolateral PFC areas, whereas patients showed a preference for HSF information or no preference. RSFC revealed a lack of connectivity between early visual areas and PFC for patients. These results demonstrate impaired processing of LSF information during object recognition in schizophrenia, with patients instead displaying increased processing of HSF information. This is consistent with findings of a preference for local over global visual information in schizophrenia. PMID:22735157

  5. Object recognition of real targets using modelled SAR images

    NASA Astrophysics Data System (ADS)

    Zherdev, D. A.

    2017-12-01

    In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

  6. Electrophysiological evidence for effects of color knowledge in object recognition.

    PubMed

    Lu, Aitao; Xu, Guiping; Jin, Hua; Mo, Lei; Zhang, Jijia; Zhang, John X

    2010-01-29

    Knowledge about the typical colors associated with familiar everyday objects (i.e., strawberries are red) is well-known to be represented in the conceptual semantic system. Evidence that such knowledge may also play a role in early perceptual processes for object recognition is scant. In the present ERP study, participants viewed a list of object pictures and detected infrequent stimulus repetitions. Results show that shortly after stimulus onset, ERP components indexing early perceptual processes, including N1, P2, and N2, differentiated between objects in their appropriate or congruent color from these objects in an inappropriate or incongruent color. Such congruence effect also occurred in N3 associated with semantic processing of pictures but not in N4 for domain-general semantic processing. Our results demonstrate a clear effect of color knowledge in early object recognition stages and support the following proposal-color as a surface property is stored in a multiple-memory system where pre-semantic perceptual and semantic conceptual representations interact during object recognition. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

  7. Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

    PubMed

    Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

    2017-10-01

    This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

  8. The uncrowded window of object recognition

    PubMed Central

    Pelli, Denis G; Tillman, Katharine A

    2009-01-01

    It is now emerging that vision is usually limited by object spacing rather than size. The visual system recognizes an object by detecting and then combining its features. ‘Crowding’ occurs when objects are too close together and features from several objects are combined into a jumbled percept. Here, we review the explosion of studies on crowding—in grating discrimination, letter and face recognition, visual search, selective attention, and reading—and find a universal principle, the Bouma law. The critical spacing required to prevent crowding is equal for all objects, although the effect is weaker between dissimilar objects. Furthermore, critical spacing at the cortex is independent of object position, and critical spacing at the visual field is proportional to object distance from fixation. The region where object spacing exceeds critical spacing is the ‘uncrowded window’. Observers cannot recognize objects outside of this window and its size limits the speed of reading and search. PMID:18828191

  9. Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

    NASA Astrophysics Data System (ADS)

    Sadjadi, Firooz A.

    1985-01-01

    A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.

  10. Distinct roles of basal forebrain cholinergic neurons in spatial and object recognition memory.

    PubMed

    Okada, Kana; Nishizawa, Kayo; Kobayashi, Tomoko; Sakata, Shogo; Kobayashi, Kazuto

    2015-08-06

    Recognition memory requires processing of various types of information such as objects and locations. Impairment in recognition memory is a prominent feature of amnesia and a symptom of Alzheimer's disease (AD). Basal forebrain cholinergic neurons contain two major groups, one localized in the medial septum (MS)/vertical diagonal band of Broca (vDB), and the other in the nucleus basalis magnocellularis (NBM). The roles of these cell groups in recognition memory have been debated, and it remains unclear how they contribute to it. We use a genetic cell targeting technique to selectively eliminate cholinergic cell groups and then test spatial and object recognition memory through different behavioural tasks. Eliminating MS/vDB neurons impairs spatial but not object recognition memory in the reference and working memory tasks, whereas NBM elimination undermines only object recognition memory in the working memory task. These impairments are restored by treatment with acetylcholinesterase inhibitors, anti-dementia drugs for AD. Our results highlight that MS/vDB and NBM cholinergic neurons are not only implicated in recognition memory but also have essential roles in different types of recognition memory.

  11. High speed optical object recognition processor with massive holographic memory

    NASA Technical Reports Server (NTRS)

    Chao, T.; Zhou, H.; Reyes, G.

    2002-01-01

    Real-time object recognition using a compact grayscale optical correlator will be introduced. A holographic memory module for storing a large bank of optimum correlation filters, to accommodate the large data throughput rate needed for many real-world applications, has also been developed. System architecture of the optical processor and the holographic memory will be presented. Application examples of this object recognition technology will also be demonstrated.

  12. On the three-quarter view advantage of familiar object recognition.

    PubMed

    Nonose, Kohei; Niimi, Ryosuke; Yokosawa, Kazuhiko

    2016-11-01

    A three-quarter view, i.e., an oblique view, of familiar objects often leads to a higher subjective goodness rating when compared with other orientations. What is the source of the high goodness for oblique views? First, we confirmed that object recognition performance was also best for oblique views around 30° view, even when the foreshortening disadvantage of front- and side-views was minimized (Experiments 1 and 2). In Experiment 3, we measured subjective ratings of view goodness and two possible determinants of view goodness: familiarity of view, and subjective impression of three-dimensionality. Three-dimensionality was measured as the subjective saliency of visual depth information. The oblique views were rated best, most familiar, and as approximating greatest three-dimensionality on average; however, the cluster analyses showed that the "best" orientation systematically varied among objects. We found three clusters of objects: front-preferred objects, oblique-preferred objects, and side-preferred objects. Interestingly, recognition performance and the three-dimensionality rating were higher for oblique views irrespective of the clusters. It appears that recognition efficiency is not the major source of the three-quarter view advantage. There are multiple determinants and variability among objects. This study suggests that the classical idea that a canonical view has a unique advantage in object perception requires further discussion.

  13. Superior voice recognition in a patient with acquired prosopagnosia and object agnosia.

    PubMed

    Hoover, Adria E N; Démonet, Jean-François; Steeves, Jennifer K E

    2010-11-01

    Anecdotally, it has been reported that individuals with acquired prosopagnosia compensate for their inability to recognize faces by using other person identity cues such as hair, gait or the voice. Are they therefore superior at the use of non-face cues, specifically voices, to person identity? Here, we empirically measure person and object identity recognition in a patient with acquired prosopagnosia and object agnosia. We quantify person identity (face and voice) and object identity (car and horn) recognition for visual, auditory, and bimodal (visual and auditory) stimuli. The patient is unable to recognize faces or cars, consistent with his prosopagnosia and object agnosia, respectively. He is perfectly able to recognize people's voices and car horns and bimodal stimuli. These data show a reverse shift in the typical weighting of visual over auditory information for audiovisual stimuli in a compromised visual recognition system. Moreover, the patient shows selectively superior voice recognition compared to the controls revealing that two different stimulus domains, persons and objects, may not be equally affected by sensory adaptation effects. This also implies that person and object identity recognition are processed in separate pathways. These data demonstrate that an individual with acquired prosopagnosia and object agnosia can compensate for the visual impairment and become quite skilled at using spared aspects of sensory processing. In the case of acquired prosopagnosia it is advantageous to develop a superior use of voices for person identity recognition in everyday life. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Tactile recognition and localization using object models: the case of polyhedra on a plane.

    PubMed

    Gaston, P C; Lozano-Perez, T

    1984-03-01

    This paper discusses how data from multiple tactile sensors may be used to identify and locate one object, from among a set of known objects. We use only local information from sensors: 1) the position of contact points and 2) ranges of surface normals at the contact points. The recognition and localization process is structured as the development and pruning of a tree of consistent hypotheses about pairings between contact points and object surfaces. In this paper, we deal with polyhedral objects constrained to lie on a known plane, i.e., having three degrees of positioning freedom relative to the sensors. We illustrate the performance of the algorithm by simulation.

  15. Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane.

    DTIC Science & Technology

    1983-03-01

    poor force resolution, but high spatial resolution. We feel that the viability of this recognition approach has important implications on the design of...of the touched object: 1. Surface point - On the basis of sensor readings, some points on the sensor can be identified as being in contact with...the sensor’s shape and location in space are known, one can determine the position of some point on the touched object, to within some uncertainty

  16. Formal implementation of a performance evaluation model for the face recognition system.

    PubMed

    Shin, Yong-Nyuo; Kim, Jason; Lee, Yong-Jun; Shin, Woochang; Choi, Jin-Young

    2008-01-01

    Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

  17. Object recognition and pose estimation of planar objects from range data

    NASA Technical Reports Server (NTRS)

    Pendleton, Thomas W.; Chien, Chiun Hong; Littlefield, Mark L.; Magee, Michael

    1994-01-01

    The Extravehicular Activity Helper/Retriever (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, three-dimensional sensing of the operational environment and objects in the environment will therefore be essential. One of the sensors being considered to provide image data for object recognition and pose estimation is a phase-shift laser scanner. The characteristics of the data provided by this scanner have been studied and algorithms have been developed for segmenting range images into planar surfaces, extracting basic features such as surface area, and recognizing the object based on the characteristics of extracted features. Also, an approach has been developed for estimating the spatial orientation and location of the recognized object based on orientations of extracted planes and their intersection points. This paper presents some of the algorithms that have been developed for the purpose of recognizing and estimating the pose of objects as viewed by the laser scanner, and characterizes the desirability and utility of these algorithms within the context of the scanner itself, considering data quality and

  18. The Functional Architecture of Visual Object Recognition

    DTIC Science & Technology

    1991-07-01

    different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

  19. The memory state heuristic: A formal model based on repeated recognition judgments.

    PubMed

    Castela, Marta; Erdfelder, Edgar

    2017-02-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Higher-order neural network software for distortion invariant object recognition

    NASA Technical Reports Server (NTRS)

    Reid, Max B.; Spirkovska, Lilly

    1991-01-01

    The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

  1. Parts and Relations in Young Children's Shape-Based Object Recognition

    ERIC Educational Resources Information Center

    Augustine, Elaine; Smith, Linda B.; Jones, Susan S.

    2011-01-01

    The ability to recognize common objects from sparse information about geometric shape emerges during the same period in which children learn object names and object categories. Hummel and Biederman's (1992) theory of object recognition proposes that the geometric shapes of objects have two components--geometric volumes representing major object…

  2. Combining color and shape information for illumination-viewpoint invariant object recognition.

    PubMed

    Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

    2006-01-01

    In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

  3. Object recognition with severe spatial deficits in Williams syndrome: sparing and breakdown.

    PubMed

    Landau, Barbara; Hoffman, James E; Kurz, Nicole

    2006-07-01

    Williams syndrome (WS) is a rare genetic disorder that results in severe visual-spatial cognitive deficits coupled with relative sparing in language, face recognition, and certain aspects of motion processing. Here, we look for evidence for sparing or impairment in another cognitive system-object recognition. Children with WS, normal mental-age (MA) and chronological age-matched (CA) children, and normal adults viewed pictures of a large range of objects briefly presented under various conditions of degradation, including canonical and unusual orientations, and clear or blurred contours. Objects were shown as either full-color views (Experiment 1) or line drawings (Experiment 2). Across both experiments, WS and MA children performed similarly in all conditions while CA children performed better than both WS group and MA groups with unusual views. This advantage, however, was eliminated when images were also blurred. The error types and relative difficulty of different objects were similar across all participant groups. The results indicate selective sparing of basic mechanisms of object recognition in WS, together with developmental delay or arrest in recognition of objects from unusual viewpoints. These findings are consistent with the growing literature on brain abnormalities in WS which points to selective impairment in the parietal areas of the brain. As a whole, the results lend further support to the growing literature on the functional separability of object recognition mechanisms from other spatial functions, and raise intriguing questions about the link between genetic deficits and cognition.

  4. Changes in Visual Object Recognition Precede the Shape Bias in Early Noun Learning

    PubMed Central

    Yee, Meagan; Jones, Susan S.; Smith, Linda B.

    2012-01-01

    Two of the most formidable skills that characterize human beings are language and our prowess in visual object recognition. They may also be developmentally intertwined. Two experiments, a large sample cross-sectional study and a smaller sample 6-month longitudinal study of 18- to 24-month-olds, tested a hypothesized developmental link between changes in visual object representation and noun learning. Previous findings in visual object recognition indicate that children’s ability to recognize common basic level categories from sparse structural shape representations of object shape emerges between the ages of 18 and 24 months, is related to noun vocabulary size, and is lacking in children with language delay. Other research shows in artificial noun learning tasks that during this same developmental period, young children systematically generalize object names by shape, that this shape bias predicts future noun learning, and is lacking in children with language delay. The two experiments examine the developmental relation between visual object recognition and the shape bias for the first time. The results show that developmental changes in visual object recognition systematically precede the emergence of the shape bias. The results suggest a developmental pathway in which early changes in visual object recognition that are themselves linked to category learning enable the discovery of higher-order regularities in category structure and thus the shape bias in novel noun learning tasks. The proposed developmental pathway has implications for understanding the role of specific experience in the development of both visual object recognition and the shape bias in early noun learning. PMID:23227015

  5. Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

    PubMed Central

    Tian, Moqian; Grill-Spector, Kalanit

    2015-01-01

    Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

  6. Post-Training Reversible Inactivation of the Hippocampus Enhances Novel Object Recognition Memory

    ERIC Educational Resources Information Center

    Oliveira, Ana M. M.; Hawk, Joshua D.; Abel, Ted; Havekes, Robbert

    2010-01-01

    Research on the role of the hippocampus in object recognition memory has produced conflicting results. Previous studies have used permanent hippocampal lesions to assess the requirement for the hippocampus in the object recognition task. However, permanent hippocampal lesions may impact performance through effects on processes besides memory…

  7. Object recognition contributions to figure-ground organization: operations on outlines and subjective contours.

    PubMed

    Peterson, M A; Gibson, B S

    1994-11-01

    In previous research, replicated here, we found that some object recognition processes influence figure-ground organization. We have proposed that these object recognition processes operate on edges (or contours) detected early in visual processing, rather than on regions. Consistent with this proposal, influences from object recognition on figure-ground organization were previously observed in both pictures and stereograms depicting regions of different luminance, but not in random-dot stereograms, where edges arise late in processing (Peterson & Gibson, 1993). In the present experiments, we examined whether or not two other types of contours--outlines and subjective contours--enable object recognition influences on figure-ground organization. For both types of contours we observed a pattern of effects similar to that originally obtained with luminance edges. The results of these experiments are valuable for distinguishing between alternative views of the mechanisms mediating object recognition influences on figure-ground organization. In addition, in both Experiments 1 and 2, fixated regions were seen as figure longer than nonfixated regions, suggesting that fixation location must be included among the variables relevant to figure-ground organization.

  8. Progestogens’ effects and mechanisms for object recognition memory across the lifespan

    PubMed Central

    Walf, Alicia A.; Koonce, Carolyn J.; Frye, Cheryl A.

    2016-01-01

    This review explores the effects of female reproductive hormones, estrogens and progestogens, with a focus on progesterone and allopregnanolone, on object memory. Progesterone and its metabolites, in particular allopregnanolone, exert various effects on both cognitive and non-mnemonic functions in females. The well-known object recognition task is a valuable experimental paradigm that can be used to determine the effects and mechanisms of progestogens for mnemonic effects across the lifespan, which will be discussed herein. In this task there is little test-decay when different objects are used as targets and baseline valance for objects is controlled. This allows repeated testing, within-subjects designs, and longitudinal assessments, which aid understanding of changes in hormonal milieu. Objects are not aversive or food-based, which are hormone-sensitive factors. This review focuses on published data from our laboratory, and others, using the object recognition task in rodents to assess the role and mechanisms of progestogens throughout the lifespan. Improvements in object recognition performance of rodents are often associated with higher hormone levels in the hippocampus and prefrontal cortex during natural cycles, with hormone replacement following ovariectomy in young animals, or with aging. The capacity for reversal of age- and reproductive senescence-related decline in cognitive performance, and changes in neural plasticity that may be dissociated from peripheral effects with such decline, are discussed. The focus here will be on the effects of brain-derived factors, such as the neurosteroid, allopregnanolone, and other hormones, for enhancing object recognition across the lifespan. PMID:26235328

  9. A new method of edge detection for object recognition

    USGS Publications Warehouse

    Maddox, Brian G.; Rhew, Benjamin

    2004-01-01

    Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

  10. A Comparison of the Effects of Depth Rotation on Visual and Haptic Three-Dimensional Object Recognition

    ERIC Educational Resources Information Center

    Lawson, Rebecca

    2009-01-01

    A sequential matching task was used to compare how the difficulty of shape discrimination influences the achievement of object constancy for depth rotations across haptic and visual object recognition. Stimuli were nameable, 3-dimensional plastic models of familiar objects (e.g., bed, chair) and morphs midway between these endpoint shapes (e.g., a…

  11. An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors

    PubMed Central

    Liu, Zhong; Zhao, Changchen; Wu, Xingming; Chen, Weihai

    2017-01-01

    RGB-D sensors have been widely used in various areas of computer vision and graphics. A good descriptor will effectively improve the performance of operation. This article further analyzes the recognition performance of shape features extracted from multi-modality source data using RGB-D sensors. A hybrid shape descriptor is proposed as a representation of objects for recognition. We first extracted five 2D shape features from contour-based images and five 3D shape features over point cloud data to capture the global and local shape characteristics of an object. The recognition performance was tested for category recognition and instance recognition. Experimental results show that the proposed shape descriptor outperforms several common global-to-global shape descriptors and is comparable to some partial-to-global shape descriptors that achieved the best accuracies in category and instance recognition. Contribution of partial features and computational complexity were also analyzed. The results indicate that the proposed shape features are strong cues for object recognition and can be combined with other features to boost accuracy. PMID:28245553

  12. Development of visuo-haptic transfer for object recognition in typical preschool and school-aged children.

    PubMed

    Purpura, Giulia; Cioni, Giovanni; Tinelli, Francesca

    2018-07-01

    Object recognition is a long and complex adaptive process and its full maturation requires combination of many different sensory experiences as well as cognitive abilities to manipulate previous experiences in order to develop new percepts and subsequently to learn from the environment. It is well recognized that the transfer of visual and haptic information facilitates object recognition in adults, but less is known about development of this ability. In this study, we explored the developmental course of object recognition capacity in children using unimodal visual information, unimodal haptic information, and visuo-haptic information transfer in children from 4 years to 10 years and 11 months of age. Participants were tested through a clinical protocol, involving visual exploration of black-and-white photographs of common objects, haptic exploration of real objects, and visuo-haptic transfer of these two types of information. Results show an age-dependent development of object recognition abilities for visual, haptic, and visuo-haptic modalities. A significant effect of time on development of unimodal and crossmodal recognition skills was found. Moreover, our data suggest that multisensory processes for common object recognition are active at 4 years of age. They facilitate recognition of common objects, and, although not fully mature, are significant in adaptive behavior from the first years of age. The study of typical development of visuo-haptic processes in childhood is a starting point for future studies regarding object recognition in impaired populations.

  13. Cultural differences in visual object recognition in 3-year-old children

    PubMed Central

    Kuwabara, Megumi; Smith, Linda B.

    2016-01-01

    Recent research indicates that culture penetrates fundamental processes of perception and cognition (e.g. Nisbett & Miyamoto, 2005). Here, we provide evidence that these influences begin early and influence how preschool children recognize common objects. The three tasks (n=128) examined the degree to which nonface object recognition by 3 year olds was based on individual diagnostic features versus more configural and holistic processing. Task 1 used a 6-alternative forced choice task in which children were asked to find a named category in arrays of masked objects in which only 3 diagnostic features were visible for each object. U.S. children outperformed age-matched Japanese children. Task 2 presented pictures of objects to children piece by piece. U.S. children recognized the objects given fewer pieces than Japanese children and likelihood of recognition increased for U.S., but not Japanese children when the piece added was rated by both U.S. and Japanese adults as highly defining. Task 3 used a standard measure of configural progressing, asking the degree to which recognition of matching pictures was disrupted by the rotation of one picture. Japanese children’s recognition was more disrupted by inversion than was that of U.S. children, indicating more configural processing by Japanese than U.S. children. The pattern suggests early cross-cultural differences in visual processing; findings that raise important questions about how visual experiences differ across cultures and about universal patterns of cognitive development. PMID:26985576

  14. Cultural differences in visual object recognition in 3-year-old children.

    PubMed

    Kuwabara, Megumi; Smith, Linda B

    2016-07-01

    Recent research indicates that culture penetrates fundamental processes of perception and cognition. Here, we provide evidence that these influences begin early and influence how preschool children recognize common objects. The three tasks (N=128) examined the degree to which nonface object recognition by 3-year-olds was based on individual diagnostic features versus more configural and holistic processing. Task 1 used a 6-alternative forced choice task in which children were asked to find a named category in arrays of masked objects where only three diagnostic features were visible for each object. U.S. children outperformed age-matched Japanese children. Task 2 presented pictures of objects to children piece by piece. U.S. children recognized the objects given fewer pieces than Japanese children, and the likelihood of recognition increased for U.S. children, but not Japanese children, when the piece added was rated by both U.S. and Japanese adults as highly defining. Task 3 used a standard measure of configural progressing, asking the degree to which recognition of matching pictures was disrupted by the rotation of one picture. Japanese children's recognition was more disrupted by inversion than was that of U.S. children, indicating more configural processing by Japanese than U.S. children. The pattern suggests early cross-cultural differences in visual processing; findings that raise important questions about how visual experiences differ across cultures and about universal patterns of cognitive development. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Leveraging Cognitive Context for Object Recognition

    DTIC Science & Technology

    2014-06-01

    learned from large image databases. We build upon this concept by exploring cognitive context, demonstrating how rich dynamic context provided by...context that people rely upon as they perceive the world. Context in ACT-R/E takes the form of associations between related concepts that are learned ...and accuracy of object recognition. Context is most often viewed as a static concept, learned from large image databases. We build upon this concept by

  16. Ultra-FDst Object Recognition from Few Spikes

    DTIC Science & Technology

    2005-07-01

    Ultra-fast Object Recognition from Few Spikes Chou Hung, Gabriel Kreiman , Tomaso Poggio & James J. DiCarlo AI Memo 2005-022 July 2005 CBCL Memo 253...authors, Chou Hung and Gabriel Kreiman , contributed equally to this work. Supplementary Material is available at http://ramonycajal.mit.edu... kreiman /resources/ultrafast/. _____________________________________________________________________________ This report describes research done at

  17. Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

    PubMed

    Markman, Adam; Shen, Xin; Hua, Hong; Javidi, Bahram

    2016-01-15

    An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window. A support vector machine (SVM) is then used for classification. Once an object has been identified, the 3D reconstructed scene with the detected object is optically displayed in the smartglasses allowing the user to see the object, remove partial occlusions of the object, and provide critical information about the object such as 3D coordinates, which are not possible with conventional AR devices. To the best of our knowledge, this is the first report on combining axially distributed sensing with 3D object visualization and recognition for applications to augmented reality. The proposed approach can have benefits for many applications, including medical, military, transportation, and manufacturing.

  18. Implicit and Explicit Contributions to Object Recognition: Evidence from Rapid Perceptual Learning

    PubMed Central

    Hassler, Uwe; Friese, Uwe; Gruber, Thomas

    2012-01-01

    The present study investigated implicit and explicit recognition processes of rapidly perceptually learned objects by means of steady-state visual evoked potentials (SSVEP). Participants were initially exposed to object pictures within an incidental learning task (living/non-living categorization). Subsequently, degraded versions of some of these learned pictures were presented together with degraded versions of unlearned pictures and participants had to judge, whether they recognized an object or not. During this test phase, stimuli were presented at 15 Hz eliciting an SSVEP at the same frequency. Source localizations of SSVEP effects revealed for implicit and explicit processes overlapping activations in orbito-frontal and temporal regions. Correlates of explicit object recognition were additionally found in the superior parietal lobe. These findings are discussed to reflect facilitation of object-specific processing areas within the temporal lobe by an orbito-frontal top-down signal as proposed by bi-directional accounts of object recognition. PMID:23056558

  19. Estrous cycle, pregnancy, and parity enhance performance of rats in object recognition or object placement tasks

    PubMed Central

    Paris, Jason J; Frye, Cheryl A

    2008-01-01

    Ovarian hormone elevations are associated with enhanced learning/memory. During behavioral estrus or pregnancy, progestins, such as progesterone (P4) and its metabolite 5α-pregnan-3α-ol-20-one (3α,5α-THP), are elevated due, in part, to corpora luteal and placental secretion. During ‘pseudopregnancy’, the induction of corpora luteal functioning results in a hormonal milieu analogous to pregnancy, which ceases after about 12 days, due to the lack of placental formation. Multiparity is also associated with enhanced learning/memory, perhaps due to prior steroid exposure during pregnancy. Given evidence that progestins and/or parity may influence cognition, we investigated how natural alterations in the progestin milieu influence cognitive performance. In Experiment 1, virgin rats (nulliparous) or rats with two prior pregnancies (multiparous) were assessed on the object placement and recognition tasks, when in high-estrogen/P4 (behavioral estrus) or low-estrogen/P4 (diestrus) phases of the estrous cycle. In Experiment 2, primiparous or multiparous rats were tested in the object placement and recognition tasks when not pregnant, pseudopregnant, or pregnant (between gestational days (GDs) 6 and 12). In Experiment 3, pregnant primiparous or multiparous rats were assessed daily in the object placement or recognition tasks. Females in natural states associated with higher endogenous progestins (behavioral estrus, pregnancy, multiparity) outperformed rats in low progestin states (diestrus, non-pregnancy, nulliparity) on the object placement and recognition tasks. In earlier pregnancy, multiparous, compared with primiparous, rats had a lower corticosterone, but higher estrogen levels, concomitant with better object placement performance. From GD 13 until post partum, primiparous rats had higher 3α,5α-THP levels and improved object placement performance compared with multiparous rats. PMID:18390689

  20. Neural Substrates of View-Invariant Object Recognition Developed without Experiencing Rotations of the Objects

    PubMed Central

    Okamura, Jun-ya; Yamaguchi, Reona; Honda, Kazunari; Tanaka, Keiji

    2014-01-01

    One fails to recognize an unfamiliar object across changes in viewing angle when it must be discriminated from similar distractor objects. View-invariant recognition gradually develops as the viewer repeatedly sees the objects in rotation. It is assumed that different views of each object are associated with one another while their successive appearance is experienced in rotation. However, natural experience of objects also contains ample opportunities to discriminate among objects at each of the multiple viewing angles. Our previous behavioral experiments showed that after experiencing a new set of object stimuli during a task that required only discrimination at each of four viewing angles at 30° intervals, monkeys could recognize the objects across changes in viewing angle up to 60°. By recording activities of neurons from the inferotemporal cortex after various types of preparatory experience, we here found a possible neural substrate for the monkeys' performance. For object sets that the monkeys had experienced during the task that required only discrimination at each of four viewing angles, many inferotemporal neurons showed object selectivity covering multiple views. The degree of view generalization found for these object sets was similar to that found for stimulus sets with which the monkeys had been trained to conduct view-invariant recognition. These results suggest that the experience of discriminating new objects in each of several viewing angles develops the partially view-generalized object selectivity distributed over many neurons in the inferotemporal cortex, which in turn bases the monkeys' emergent capability to discriminate the objects across changes in viewing angle. PMID:25378169

  1. View-invariant object recognition ability develops after discrimination, not mere exposure, at several viewing angles.

    PubMed

    Yamashita, Wakayo; Wang, Gang; Tanaka, Keiji

    2010-01-01

    One usually fails to recognize an unfamiliar object across changes in viewing angle when it has to be discriminated from similar distractor objects. Previous work has demonstrated that after long-term experience in discriminating among a set of objects seen from the same viewing angle, immediate recognition of the objects across 30-60 degrees changes in viewing angle becomes possible. The capability for view-invariant object recognition should develop during the within-viewing-angle discrimination, which includes two kinds of experience: seeing individual views and discriminating among the objects. The aim of the present study was to determine the relative contribution of each factor to the development of view-invariant object recognition capability. Monkeys were first extensively trained in a task that required view-invariant object recognition (Object task) with several sets of objects. The animals were then exposed to a new set of objects over 26 days in one of two preparatory tasks: one in which each object view was seen individually, and a second that required discrimination among the objects at each of four viewing angles. After the preparatory period, we measured the monkeys' ability to recognize the objects across changes in viewing angle, by introducing the object set to the Object task. Results indicated significant view-invariant recognition after the second but not first preparatory task. These results suggest that discrimination of objects from distractors at each of several viewing angles is required for the development of view-invariant recognition of the objects when the distractors are similar to the objects.

  2. Joint object and action recognition via fusion of partially observable surveillance imagery data

    NASA Astrophysics Data System (ADS)

    Shirkhodaie, Amir; Chan, Alex L.

    2017-05-01

    Partially observable group activities (POGA) occurring in confined spaces are epitomized by their limited observability of the objects and actions involved. In many POGA scenarios, different objects are being used by human operators for the conduct of various operations. In this paper, we describe the ontology of such as POGA in the context of In-Vehicle Group Activity (IVGA) recognition. Initially, we describe the virtue of ontology modeling in the context of IVGA and show how such an ontology and a priori knowledge about the classes of in-vehicle activities can be fused for inference of human actions that consequentially leads to understanding of human activity inside the confined space of a vehicle. In this paper, we treat the problem of "action-object" as a duality problem. We postulate a correlation between observed human actions and the object that is being utilized within those actions, and conversely, if an object being handled is recognized, we may be able to expect a number of actions that are likely to be performed on that object. In this study, we use partially observable human postural sequences to recognition actions. Inspired by convolutional neural networks (CNNs) learning capability, we present an architecture design using a new CNN model to learn "action-object" perception from surveillance videos. In this study, we apply a sequential Deep Hidden Markov Model (DHMM) as a post-processor to CNN to decode realized observations into recognized actions and activities. To generate the needed imagery data set for the training and testing of these new methods, we use the IRIS virtual simulation software to generate high-fidelity and dynamic animated scenarios that depict in-vehicle group activities under different operational contexts. The results of our comparative investigation are discussed and presented in detail.

  3. Deletion of the GluA1 AMPA receptor subunit impairs recency-dependent object recognition memory

    PubMed Central

    Sanderson, David J.; Hindley, Emma; Smeaton, Emily; Denny, Nick; Taylor, Amy; Barkus, Chris; Sprengel, Rolf; Seeburg, Peter H.; Bannerman, David M.

    2011-01-01

    Deletion of the GluA1 AMPA receptor subunit impairs short-term spatial recognition memory. It has been suggested that short-term recognition depends upon memory caused by the recent presentation of a stimulus that is independent of contextual–retrieval processes. The aim of the present set of experiments was to test whether the role of GluA1 extends to nonspatial recognition memory. Wild-type and GluA1 knockout mice were tested on the standard object recognition task and a context-independent recognition task that required recency-dependent memory. In a first set of experiments it was found that GluA1 deletion failed to impair performance on either of the object recognition or recency-dependent tasks. However, GluA1 knockout mice displayed increased levels of exploration of the objects in both the sample and test phases compared to controls. In contrast, when the time that GluA1 knockout mice spent exploring the objects was yoked to control mice during the sample phase, it was found that GluA1 deletion now impaired performance on both the object recognition and the recency-dependent tasks. GluA1 deletion failed to impair performance on a context-dependent recognition task regardless of whether object exposure in knockout mice was yoked to controls or not. These results demonstrate that GluA1 is necessary for nonspatial as well as spatial recognition memory and plays an important role in recency-dependent memory processes. PMID:21378100

  4. Plastic modifications induced by object recognition memory processing

    PubMed Central

    Clarke, Julia Rosauro; Cammarota, Martín; Gruart, Agnès; Izquierdo, Iván; Delgado-García, José María

    2010-01-01

    Long-term potentiation (LTP) phenomenon is widely accepted as a cellular model of memory consolidation. Object recognition (OR) is a particularly useful way of studying declarative memory in rodents because it makes use of their innate preference for novel over familiar objects. In this study, mice had electrodes implanted in the hippocampal Schaffer collaterals–pyramidal CA1 pathway and were trained for OR. Field EPSPs evoked at the CA3-CA1 synapse were recorded at the moment of training and at different times thereafter. LTP-like synaptic enhancement was found 6 h posttraining. A testing session was conducted 24 h after training, in the presence of one familiar and one novel object. Hippocampal synaptic facilitation was observed during exploration of familiar and novel objects. A short depotentiation period was observed early after the test and was followed by a later phase of synaptic efficacy enhancement. Here, we show that OR memory consolidation is accompanied by transient potentiation in the hippocampal CA3-CA1 synapses, while reconsolidation of this memory requires a short-lasting phase of depotentiation that could account for its well described vulnerability. The late synaptic enhancement phase, on the other hand, would be a consequence of memory restabilization. PMID:20133798

  5. Global precedence effects account for individual differences in both face and object recognition performance.

    PubMed

    Gerlach, Christian; Starrfelt, Randi

    2018-03-20

    There has been an increase in studies adopting an individual difference approach to examine visual cognition and in particular in studies trying to relate face recognition performance with measures of holistic processing (the face composite effect and the part-whole effect). In the present study we examine whether global precedence effects, measured by means of non-face stimuli in Navon's paradigm, can also account for individual differences in face recognition and, if so, whether the effect is of similar magnitude for faces and objects. We find evidence that global precedence effects facilitate both face and object recognition, and to a similar extent. Our results suggest that both face and object recognition are characterized by a coarse-to-fine temporal dynamic, where global shape information is derived prior to local shape information, and that the efficiency of face and object recognition is related to the magnitude of the global precedence effect.

  6. Object recognition for autonomous robot utilizing distributed knowledge database

    NASA Astrophysics Data System (ADS)

    Takatori, Jiro; Suzuki, Kenji; Hartono, Pitoyo; Hashimoto, Shuji

    2003-10-01

    In this paper we present a novel method of object recognition utilizing a remote knowledge database for an autonomous robot. The developed robot has three robot arms with different sensors; two CCD cameras and haptic sensors. It can see, touch and move the target object from different directions. Referring to remote knowledge database of geometry and material, the robot observes and handles the objects to understand them including their physical characteristics.

  7. Traffic Behavior Recognition Using the Pachinko Allocation Model

    PubMed Central

    Huynh-The, Thien; Banos, Oresti; Le, Ba-Vui; Bui, Dinh-Mao; Yoon, Yongik; Lee, Sungyoung

    2015-01-01

    CCTV-based behavior recognition systems have gained considerable attention in recent years in the transportation surveillance domain for identifying unusual patterns, such as traffic jams, accidents, dangerous driving and other abnormal behaviors. In this paper, a novel approach for traffic behavior modeling is presented for video-based road surveillance. The proposed system combines the pachinko allocation model (PAM) and support vector machine (SVM) for a hierarchical representation and identification of traffic behavior. A background subtraction technique using Gaussian mixture models (GMMs) and an object tracking mechanism based on Kalman filters are utilized to firstly construct the object trajectories. Then, the sparse features comprising the locations and directions of the moving objects are modeled by PAM into traffic topics, namely activities and behaviors. As a key innovation, PAM captures not only the correlation among the activities, but also among the behaviors based on the arbitrary directed acyclic graph (DAG). The SVM classifier is then utilized on top to train and recognize the traffic activity and behavior. The proposed model shows more flexibility and greater expressive power than the commonly-used latent Dirichlet allocation (LDA) approach, leading to a higher recognition accuracy in the behavior classification. PMID:26151213

  8. Neural substrates of view-invariant object recognition developed without experiencing rotations of the objects.

    PubMed

    Okamura, Jun-Ya; Yamaguchi, Reona; Honda, Kazunari; Wang, Gang; Tanaka, Keiji

    2014-11-05

    One fails to recognize an unfamiliar object across changes in viewing angle when it must be discriminated from similar distractor objects. View-invariant recognition gradually develops as the viewer repeatedly sees the objects in rotation. It is assumed that different views of each object are associated with one another while their successive appearance is experienced in rotation. However, natural experience of objects also contains ample opportunities to discriminate among objects at each of the multiple viewing angles. Our previous behavioral experiments showed that after experiencing a new set of object stimuli during a task that required only discrimination at each of four viewing angles at 30° intervals, monkeys could recognize the objects across changes in viewing angle up to 60°. By recording activities of neurons from the inferotemporal cortex after various types of preparatory experience, we here found a possible neural substrate for the monkeys' performance. For object sets that the monkeys had experienced during the task that required only discrimination at each of four viewing angles, many inferotemporal neurons showed object selectivity covering multiple views. The degree of view generalization found for these object sets was similar to that found for stimulus sets with which the monkeys had been trained to conduct view-invariant recognition. These results suggest that the experience of discriminating new objects in each of several viewing angles develops the partially view-generalized object selectivity distributed over many neurons in the inferotemporal cortex, which in turn bases the monkeys' emergent capability to discriminate the objects across changes in viewing angle. Copyright © 2014 the authors 0270-6474/14/3415047-13$15.00/0.

  9. Viewpoint-Specific Representations in Three-Dimensional Object Recognition

    DTIC Science & Technology

    1990-08-01

    for useful suggestions and illuminating discuc- sions, and Ellen Hildreth for her comments on a draft of this repcrt. References [1] 1. Biederman ...1982. [24] I. Rock and J. DiVita. A case of viewer-centered object perception. Cognitive Psychology, 19:280-293, 1987 . [25] I. Rock, D. Wheeler, and...Raleigh, NC, 1987 . [30] S. Ullman. Aligning pictorial descriptions: an approach to object recognition. Cognition, 32:193-254, 1989. [31] S. UUman and R

  10. Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.

    PubMed

    Kheradpisheh, Saeed R; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

    2016-01-01

    View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth) as well as their magnitude, which we call "variation level." We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group) on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier). This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.

  11. Single-pixel non-imaging object recognition by means of Fourier spectrum acquisition

    NASA Astrophysics Data System (ADS)

    Chen, Huichao; Shi, Jianhong; Liu, Xialin; Niu, Zhouzhou; Zeng, Guihua

    2018-04-01

    Single-pixel imaging has emerged over recent years as a novel imaging technique, which has significant application prospects. In this paper, we propose and experimentally demonstrate a scheme that can achieve single-pixel non-imaging object recognition by acquiring the Fourier spectrum. In an experiment, a four-step phase-shifting sinusoid illumination light is used to irradiate the object image, the value of the light intensity is measured with a single-pixel detection unit, and the Fourier coefficients of the object image are obtained by a differential measurement. The Fourier coefficients are first cast into binary numbers to obtain the hash value. We propose a new method of perceptual hashing algorithm, which is combined with a discrete Fourier transform to calculate the hash value. The hash distance is obtained by calculating the difference of the hash value between the object image and the contrast images. By setting an appropriate threshold, the object image can be quickly and accurately recognized. The proposed scheme realizes single-pixel non-imaging perceptual hashing object recognition by using fewer measurements. Our result might open a new path for realizing object recognition with non-imaging.

  12. Speckle-learning-based object recognition through scattering media.

    PubMed

    Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

    2015-12-28

    We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

  13. Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

    PubMed

    Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

    2010-11-01

    Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

  14. Critical object recognition in millimeter-wave images with robustness to rotation and scale.

    PubMed

    Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

    2017-06-01

    Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

  15. The Vanderbilt Expertise Test Reveals Domain-General and Domain-Specific Sex Effects in Object Recognition

    PubMed Central

    McGugin, Rankin W.; Richler, Jennifer J.; Herzmann, Grit; Speegle, Magen; Gauthier, Isabel

    2012-01-01

    Individual differences in face recognition are often contrasted with differences in object recognition using a single object category. Likewise, individual differences in perceptual expertise for a given object domain have typically been measured relative to only a single category baseline. In Experiment 1, we present a new test of object recognition, the Vanderbilt Expertise Test (VET), which is comparable in methods to the Cambridge Face Memory Task (CFMT) but uses eight different object categories. Principal component analysis reveals that the underlying structure of the VET can be largely explained by two independent factors, which demonstrate good reliability and capture interesting sex differences inherent in the VET structure. In Experiment 2, we show how the VET can be used to separate domain-specific from domain-general contributions to a standard measure of perceptual expertise. While domain-specific contributions are found for car matching for both men and women and for plane matching in men, women in this sample appear to use more domain-general strategies to match planes. In Experiment 3, we use the VET to demonstrate that holistic processing of faces predicts face recognition independently of general object recognition ability, which has a sex-specific contribution to face recognition. Overall, the results suggest that the VET is a reliable and valid measure of object recognition abilities and can measure both domain-general skills and domain-specific expertise, which were both found to depend on the sex of observers. PMID:22877929

  16. Auditory-visual object recognition time suggests specific processing for animal sounds.

    PubMed

    Suied, Clara; Viaud-Delmon, Isabelle

    2009-01-01

    Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.

  17. Stereo Viewing Modulates Three-Dimensional Shape Processing During Object Recognition: A High-Density ERP Study

    PubMed Central

    2017-01-01

    The role of stereo disparity in the recognition of 3-dimensional (3D) object shape remains an unresolved issue for theoretical models of the human visual system. We examined this issue using high-density (128 channel) recordings of event-related potentials (ERPs). A recognition memory task was used in which observers were trained to recognize a subset of complex, multipart, 3D novel objects under conditions of either (bi-) monocular or stereo viewing. In a subsequent test phase they discriminated previously trained targets from untrained distractor objects that shared either local parts, 3D spatial configuration, or neither dimension, across both previously seen and novel viewpoints. The behavioral data showed a stereo advantage for target recognition at untrained viewpoints. ERPs showed early differential amplitude modulations to shape similarity defined by local part structure and global 3D spatial configuration. This occurred initially during an N1 component around 145–190 ms poststimulus onset, and then subsequently during an N2/P3 component around 260–385 ms poststimulus onset. For mono viewing, amplitude modulation during the N1 was greatest between targets and distracters with different local parts for trained views only. For stereo viewing, amplitude modulation during the N2/P3 was greatest between targets and distracters with different global 3D spatial configurations and generalized across trained and untrained views. The results show that image classification is modulated by stereo information about the local part, and global 3D spatial configuration of object shape. The findings challenge current theoretical models that do not attribute functional significance to stereo input during the computation of 3D object shape. PMID:29022728

  18. Intraperirhinal cortex administration of the synthetic cannabinoid, HU210, disrupts object recognition memory in rats.

    PubMed

    Sticht, Martin A; Jacklin, Derek L; Mechoulam, Raphael; Parker, Linda A; Winters, Boyer D

    2015-03-25

    Cannabinoids disrupt learning and memory in human and nonhuman participants. Object recognition memory, which is particularly susceptible to the impairing effects of cannabinoids, relies critically on the perirhinal cortex (PRh); however, to date, the effects of cannabinoids within PRh have not been assessed. In the present study, we evaluated the effects of localized administration of the synthetic cannabinoid, HU210 (0.01, 1.0 μg/hemisphere), into PRh on spontaneous object recognition in Long-Evans rats. Animals received intra-PRh infusions of HU210 before the sample phase, and object recognition memory was assessed at various delays in a subsequent retention test. We found that presample intra-PRh HU210 dose dependently (1.0 μg but not 0.01 μg) interfered with spontaneous object recognition performance, exerting an apparently more pronounced effect when memory demands were increased. These novel findings show that cannabinoid agonists in PRh disrupt object recognition memory. Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.

  19. Dietary effects on object recognition: The impact of high-fat high-sugar diets on recollection and familiarity-based memory.

    PubMed

    Tran, Dominic M D; Westbrook, R Frederick

    2018-05-31

    Exposure to a high-fat high-sugar (HFHS) diet rapidly impairs novel-place- but not novel-object-recognition memory in rats (Tran & Westbrook, 2015, 2017). Three experiments sought to investigate the generality of diet-induced cognitive deficits by examining whether there are conditions under which object-recognition memory is impaired. Experiments 1 and 3 tested the strength of short- and long-term object-memory trace, respectively, by varying the interval of time between object familiarization and subsequent novel object test. Experiment 2 tested the effect of increasing working memory load on object-recognition memory by interleaving additional object exposures between familiarization and test in an n-back style task. Experiments 1-3 failed to detect any differences in object recognition between HFHS and control rats. Experiment 4 controlled for object novelty by separately familiarizing both objects presented at test, which included one remote-familiar and one recent-familiar object. Under these conditions, when test objects differed in their relative recency, HFHS rats showed a weaker memory trace for the remote object compared to chow rats. This result suggests that the diet leaves intact recollection judgments, but impairs familiarity judgments. We speculate that the HFHS diet adversely affects "where" memories as well as the quality of "what" memories, and discuss these effects in relation to recollection and familiarity memory models, hippocampal-dependent functions, and episodic food memories. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Neurophysiological indices of perceptual object priming in the absence of explicit recognition memory.

    PubMed

    Harris, Jill D; Cutmore, Tim R H; O'Gorman, John; Finnigan, Simon; Shum, David

    2009-02-01

    The aim of this study was to identify ERP correlates of perceptual object priming that are insensitive to factors affecting explicit, episodic memory. EEG was recorded from 21 participants while they performed a visual object recognition test on a combination of unstudied items and old items that were previously encountered during either a 'deep' or 'shallow' levels-of-processing (LOP) study task. The results demonstrated a midline P150 old/new effect which was sensitive only to objects' old/new status and not to the accuracy of recognition responses to old items, or to the LOP manipulation. Similar outcomes were observed for the subsequent P200 and N400 effects, the former of which had a parietal scalp maximum and the latter, a broadly distributed topography. In addition an LPC old/new effect typical of those reported in past ERP recognition studies was observed. These outcomes support the proposal that the P150 effect is reflective of perceptual object priming and moreover, provide novel evidence that this and the P200 effect are independent of explicit recognition memory process(es).

  1. The relationship between change detection and recognition of centrally attended objects in motion pictures.

    PubMed

    Angelone, Bonnie L; Levin, Daniel T; Simons, Daniel J

    2003-01-01

    Observers typically detect changes to central objects more readily than changes to marginal objects, but they sometimes miss changes to central, attended objects as well. However, even if observers do not report such changes, they may be able to recognize the changed object. In three experiments we explored change detection and recognition memory for several types of changes to central objects in motion pictures. Observers who failed to detect a change still performed at above chance levels on a recognition task in almost all conditions. In addition, observers who detected the change were no more accurate in their recognition than those who did not detect the change. Despite large differences in the detectability of changes across conditions, those observers who missed the change did not vary in their ability to recognize the changing object.

  2. The Neural Regions Sustaining Episodic Encoding and Recognition of Objects

    ERIC Educational Resources Information Center

    Hofer, Alex; Siedentopf, Christian M.; Ischebeck, Anja; Rettenbacher, Maria A.; Widschwendter, Christian G.; Verius, Michael; Golaszewski, Stefan M.; Koppelstaetter, Florian; Felber, Stephan; Wolfgang Fleischhacker, W.

    2007-01-01

    In this functional MRI experiment, encoding of objects was associated with activation in left ventrolateral prefrontal/insular and right dorsolateral prefrontal and fusiform regions as well as in the left putamen. By contrast, correct recognition of previously learned objects (R judgments) produced activation in left superior frontal, bilateral…

  3. A Single-System Model Predicts Recognition Memory and Repetition Priming in Amnesia

    PubMed Central

    Kessels, Roy P.C.; Wester, Arie J.; Shanks, David R.

    2014-01-01

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. PMID:25122896

  4. Development of novel tasks for studying view-invariant object recognition in rodents: Sensitivity to scopolamine.

    PubMed

    Mitchnick, Krista A; Wideman, Cassidy E; Huff, Andrew E; Palmer, Daniel; McNaughton, Bruce L; Winters, Boyer D

    2018-05-15

    The capacity to recognize objects from different view-points or angles, referred to as view-invariance, is an essential process that humans engage in daily. Currently, the ability to investigate the neurobiological underpinnings of this phenomenon is limited, as few ethologically valid view-invariant object recognition tasks exist for rodents. Here, we report two complementary, novel view-invariant object recognition tasks in which rodents physically interact with three-dimensional objects. Prior to experimentation, rats and mice were given extensive experience with a set of 'pre-exposure' objects. In a variant of the spontaneous object recognition task, novelty preference for pre-exposed or new objects was assessed at various angles of rotation (45°, 90° or 180°); unlike control rodents, for whom the objects were novel, rats and mice tested with pre-exposed objects did not discriminate between rotated and un-rotated objects in the choice phase, indicating substantial view-invariant object recognition. Secondly, using automated operant touchscreen chambers, rats were tested on pre-exposed or novel objects in a pairwise discrimination task, where the rewarded stimulus (S+) was rotated (180°) once rats had reached acquisition criterion; rats tested with pre-exposed objects re-acquired the pairwise discrimination following S+ rotation more effectively than those tested with new objects. Systemic scopolamine impaired performance on both tasks, suggesting involvement of acetylcholine at muscarinic receptors in view-invariant object processing. These tasks present novel means of studying the behavioral and neural bases of view-invariant object recognition in rodents. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Standard object recognition memory and "what" and "where" components: Improvement by post-training epinephrine in highly habituated rats.

    PubMed

    Jurado-Berbel, Patricia; Costa-Miserachs, David; Torras-Garcia, Meritxell; Coll-Andreu, Margalida; Portell-Cortés, Isabel

    2010-02-11

    The present work examined whether post-training systemic epinephrine (EPI) is able to modulate short-term (3h) and long-term (24 h and 48 h) memory of standard object recognition, as well as long-term (24 h) memory of separate "what" (object identity) and "where" (object location) components of object recognition. Although object recognition training is associated to low arousal levels, all the animals received habituation to the training box in order to further reduce emotional arousal. Post-training EPI improved long-term (24 h and 48 h), but not short-term (3 h), memory in the standard object recognition task, as well as 24 h memory for both object identity and object location. These data indicate that post-training epinephrine: (1) facilitates long-term memory for standard object recognition; (2) exerts separate facilitatory effects on "what" (object identity) and "where" (object location) components of object recognition; and (3) is capable of improving memory for a low arousing task even in highly habituated rats.

  6. Orientation-Invariant Object Recognition: Evidence from Repetition Blindness

    ERIC Educational Resources Information Center

    Harris, Irina M.; Dux, Paul E.

    2005-01-01

    The question of whether object recognition is orientation-invariant or orientation-dependent was investigated using a repetition blindness (RB) paradigm. In RB, the second occurrence of a repeated stimulus is less likely to be reported, compared to the occurrence of a different stimulus, if it occurs within a short time of the first presentation.…

  7. It's all connected: Pathways in visual object recognition and early noun learning.

    PubMed

    Smith, Linda B

    2013-11-01

    A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  8. The subjective experience of object recognition: comparing metacognition for object detection and object categorization.

    PubMed

    Meuwese, Julia D I; van Loon, Anouk M; Lamme, Victor A F; Fahrenfort, Johannes J

    2014-05-01

    Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection).

  9. Ventromedial prefrontal cortex is obligatory for consolidation and reconsolidation of object recognition memory.

    PubMed

    Akirav, Irit; Maroun, Mouna

    2006-12-01

    Once consolidated, a long-term memory item could regain susceptibility to consolidation blockers, that is, reconsolidate, upon its reactivation. Both consolidation and reconsolidation require protein synthesis, but it is not yet known how similar these processes are in terms of molecular, cellular, and neural circuit mechanisms. Whereas most previous studies focused on aversive conditioning in the amygdala and the hippocampus, here we examine the role of the ventromedial prefrontal cortex (vmPFC) in consolidation and reconsolidation of object recognition memory. Object recognition memory is the ability to discriminate the familiarity of previously encountered objects. We found that microinfusion of the protein synthesis inhibitor anisomycin or the N-methyl-D-aspartate (NMDA) receptor antagonist D,L-2-amino-5-phosphonovaleric acid (APV) into the vmPFC, immediately after training, resulted in impairment of long-term (24 h) but not short-term (3 h) recognition memory. Similarly, microinfusion of anisomycin or APV into the vmPFC immediately after reactivation of the long-term memory impaired recognition memory 24 h, but not 3 h, post-reactivation. These results indicate that both protein synthesis and NMDA receptors are required for consolidation and reconsolidation of recognition memory in the vmPFC.

  10. A role for the CAMKK pathway in visual object recognition memory.

    PubMed

    Tinsley, Chris J; Narduzzo, Katherine E; Brown, Malcolm W; Warburton, E Clea

    2012-03-01

    The role of the CAMKK pathway in object recognition memory was investigated. Rats' performance in a preferential object recognition test was examined after local infusion into the perirhinal cortex of the CAMKK inhibitor STO-609. STO-609 infused either before or immediately after acquisition impaired memory tested after a 24 h but not a 20-min delay. Memory was not impaired when STO-609 was infused 20 min after acquisition. The expression of a downstream reaction product of CAMKK was measured by immunohistochemical staining for phospho-CAMKI(Thr177) at 10, 40, 70, and 100 min following the viewing of novel and familiar images of objects. Processing familiar images resulted in more pCAMKI stained neurons in the perirhinal cortex than processing novel images at the 10- and 40-min delays. Prior infusion of STO-609 caused a reduction in pCAMKI stained neurons in response to viewing either novel or familiar images, consistent with its role as an inhibitor of CAMKK. The results establish that the CAMKK pathway within the perirhinal cortex is important for the consolidation of object recognition memory. The activation of pCAMKI after acquisition is earlier than previously reported for pCAMKII. Copyright © 2011 Wiley Periodicals, Inc.

  11. Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

    PubMed

    Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

    2014-01-01

    The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. The research of edge extraction and target recognition based on inherent feature of objects

    NASA Astrophysics Data System (ADS)

    Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

    2008-03-01

    Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots

  13. Dopamine D1 receptor activation leads to object recognition memory in a coral reef fish.

    PubMed

    Hamilton, Trevor J; Tresguerres, Martin; Kline, David I

    2017-07-01

    Object recognition memory is the ability to identify previously seen objects and is an adaptive mechanism that increases survival for many species throughout the animal kingdom. Previously believed to be possessed by only the highest order mammals, it is now becoming clear that fish are also capable of this type of memory formation. Similar to the mammalian hippocampus, the dorsolateral pallium regulates distinct memory processes and is modulated by neurotransmitters such as dopamine. Caribbean bicolour damselfish ( Stegastes partitus ) live in complex environments dominated by coral reef structures and thus likely possess many types of complex memory abilities including object recognition. This study used a novel object recognition test in which fish were first presented two identical objects, then after a retention interval of 10 min with no objects, the fish were presented with a novel object and one of the objects they had previously encountered in the first trial. We demonstrate that the dopamine D 1 -receptor agonist (SKF 38393) induces the formation of object recognition memories in these fish. Thus, our results suggest that dopamine-receptor mediated enhancement of spatial memory formation in fish represents an evolutionarily conserved mechanism in vertebrates. © 2017 The Author(s).

  14. Anthropomorphic robot for recognition and drawing generalized object images

    NASA Astrophysics Data System (ADS)

    Ginzburg, Vera M.

    1998-10-01

    The process of recognition, for instance, understanding the text, written by different fonts, consists in the depriving of the individual attributes of the letters in the particular font. It is shown that such process, in Nature and technique, can be provided by the narrowing the spatial frequency of the object's image by its defocusing. In defocusing images remain only areas, so-called Informative Fragments (IFs), which all together form the generalized (stylized) image of many identical objects. It is shown that the variety of shapes of IFs is restricted and can be presented by `Geometrical alphabet'. The `letters' for this alphabet can be created using two basic `genetic' figures: a stripe and round spot. It is known from physiology that the special cells of visual cortex response to these particular figures. The prototype of such `genetic' alphabet has been made using Boolean algebra (Venn's diagrams). The algorithm for drawing the letter's (`genlet's') shape in this alphabet and generalized images of objects (for example, `sleeping cat'), are given. A scheme of an anthropomorphic robot is shown together with results of model computer experiment of the robot's action--`drawing' the generalized image.

  15. Picture object recognition in an American black bear (Ursus americanus).

    PubMed

    Johnson-Ulrich, Zoe; Vonk, Jennifer; Humbyrd, Mary; Crowley, Marilyn; Wojtkowski, Ela; Yates, Florence; Allard, Stephanie

    2016-11-01

    Many animals have been tested for conceptual discriminations using two-dimensional images as stimuli, and many of these species appear to transfer knowledge from 2D images to analogous real life objects. We tested an American black bear for picture-object recognition using a two alternative forced choice task. She was presented with four unique sets of objects and corresponding pictures. The bear showed generalization from both objects to pictures and pictures to objects; however, her transfer was superior when transferring from real objects to pictures, suggesting that bears can recognize visual features from real objects within photographic images during discriminations.

  16. An Approach to Object Recognition: Aligning Pictorial Descriptions.

    DTIC Science & Technology

    1986-12-01

    PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

  17. Multi-channel feature dictionaries for RGB-D object recognition

    NASA Astrophysics Data System (ADS)

    Lan, Xiaodong; Li, Qiming; Chong, Mina; Song, Jian; Li, Jun

    2018-04-01

    Hierarchical matching pursuit (HMP) is a popular feature learning method for RGB-D object recognition. However, the feature representation with only one dictionary for RGB channels in HMP does not capture sufficient visual information. In this paper, we propose multi-channel feature dictionaries based feature learning method for RGB-D object recognition. The process of feature extraction in the proposed method consists of two layers. The K-SVD algorithm is used to learn dictionaries in sparse coding of these two layers. In the first-layer, we obtain features by performing max pooling on sparse codes of pixels in a cell. And the obtained features of cells in a patch are concatenated to generate patch jointly features. Then, patch jointly features in the first-layer are used to learn the dictionary and sparse codes in the second-layer. Finally, spatial pyramid pooling can be applied to the patch jointly features of any layer to generate the final object features in our method. Experimental results show that our method with first or second-layer features can obtain a comparable or better performance than some published state-of-the-art methods.

  18. Regulation of object recognition and object placement by ovarian sex steroid hormones

    PubMed Central

    Tuscher, Jennifer J.; Fortress, Ashley M.; Kim, Jaekyoon; Frick, Karyn M.

    2014-01-01

    The ovarian hormones 17β-estradiol (E2) and progesterone (P4) are potent modulators of hippocampal memory formation. Both hormones have been demonstrated to enhance hippocampal memory by regulating the cellular and molecular mechanisms thought to underlie memory formation. Behavioral neuroendocrinologists have increasingly used the object recognition and object placement (object location) tasks to investigate the role of E2 and P4 in regulating hippocampal memory formation in rodents. These one-trial learning tasks are ideal for studying acute effects of hormone treatments on different phases of memory because they can be administered during acquisition (pre-training), consolidation (post-training), or retrieval (pre-testing). This review synthesizes the rodent literature testing the effects of E2 and P4 on object recognition (OR) and object placement (OP), and the molecular mechanisms in the hippocampus supporting memory formation in these tasks. Some general trends emerge from the data. Among gonadally intact females, object memory tends to be best when E2 and P4 levels are elevated during the estrous cycle, pregnancy, and in middle age. In ovariectomized females, E2 given before or immediately after testing generally enhances OR and OP in young and middle-aged rats and mice, although effects are mixed in aged rodents. Effects of E2 treatment on OR 7and OP memory consolidation can be mediated by both classical estrogen receptors (ERα and ERβ), and depend on glutamate receptors (NMDA, mGluR1) and activation of numerous cell signaling cascades (e.g., ERK, PI3K/Akt, mTOR) and epigenetic processes (e.g., histone H3 acetylation, DNA methylation). Acute P4 treatment given immediately after training also enhances OR and OP in young and middle-aged ovariectomized females by activating similar cell signaling pathways as E2 (e.g., ERK, mTOR). The few studies that have administered both hormones in combination suggest that treatment can enhance OR and OP, but that

  19. Grouping in object recognition: the role of a Gestalt law in letter identification.

    PubMed

    Pelli, Denis G; Majaj, Najib J; Raizman, Noah; Christian, Christopher J; Kim, Edward; Palomares, Melanie C

    2009-02-01

    The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws "prescribe for us what we are to recognize 'as one thing'" (Kohler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and "snakes in the grass" is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, "wiggle", to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping.

  20. Grouping in object recognition: The role of a Gestalt law in letter identification

    PubMed Central

    Pelli, Denis G.; Majaj, Najib J.; Raizman, Noah; Christian, Christopher J.; Kim, Edward; Palomares, Melanie C.

    2009-01-01

    The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws “prescribe for us what we are to recognize ‘as one thing’” (Köhler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and “snakes in the grass” is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, “wiggle”, to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping. PMID:19424881

  1. Intrinsic and contextual features in object recognition.

    PubMed

    Schlangen, Derrick; Barenholtz, Elan

    2015-01-28

    The context in which an object is found can facilitate its recognition. Yet, it is not known how effective this contextual information is relative to the object's intrinsic visual features, such as color and shape. To address this, we performed four experiments using rendered scenes with novel objects. In each experiment, participants first performed a visual search task, searching for a uniquely shaped target object whose color and location within the scene was experimentally manipulated. We then tested participants' tendency to use their knowledge of the location and color information in an identification task when the objects' images were degraded due to blurring, thus eliminating the shape information. In Experiment 1, we found that, in the absence of any diagnostic intrinsic features, participants identified objects based purely on their locations within the scene. In Experiment 2, we found that participants combined an intrinsic feature, color, with contextual location in order to uniquely specify an object. In Experiment 3, we found that when an object's color and location information were in conflict, participants identified the object using both sources of information equally. Finally, in Experiment 4, we found that participants used whichever source of information-either color or location-was more statistically reliable in order to identify the target object. Overall, these experiments show that the context in which objects are found can play as important a role as intrinsic features in identifying the objects. © 2015 ARVO.

  2. Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

    NASA Astrophysics Data System (ADS)

    Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

    2010-04-01

    In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

  3. Semantic attributes are encoded in human electrocorticographic signals during visual object recognition.

    PubMed

    Rupp, Kyle; Roos, Matthew; Milsap, Griffin; Caceres, Carlos; Ratto, Christopher; Chevillet, Mark; Crone, Nathan E; Wolmetz, Michael

    2017-03-01

    Non-invasive neuroimaging studies have shown that semantic category and attribute information are encoded in neural population activity. Electrocorticography (ECoG) offers several advantages over non-invasive approaches, but the degree to which semantic attribute information is encoded in ECoG responses is not known. We recorded ECoG while patients named objects from 12 semantic categories and then trained high-dimensional encoding models to map semantic attributes to spectral-temporal features of the task-related neural responses. Using these semantic attribute encoding models, untrained objects were decoded with accuracies comparable to whole-brain functional Magnetic Resonance Imaging (fMRI), and we observed that high-gamma activity (70-110Hz) at basal occipitotemporal electrodes was associated with specific semantic dimensions (manmade-animate, canonically large-small, and places-tools). Individual patient results were in close agreement with reports from other imaging modalities on the time course and functional organization of semantic processing along the ventral visual pathway during object recognition. The semantic attribute encoding model approach is critical for decoding objects absent from a training set, as well as for studying complex semantic encodings without artificially restricting stimuli to a small number of semantic categories. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Computing with Connections in Visual Recognition of Origami Objects.

    ERIC Educational Resources Information Center

    Sabbah, Daniel

    1985-01-01

    Summarizes an initial foray in tackling artificial intelligence problems using a connectionist approach. The task chosen is visual recognition of Origami objects, and the questions answered are how to construct a connectionist network to represent and recognize projected Origami line drawings and the advantages such an approach would have. (30…

  5. Adrenergic enhancement of consolidation of object recognition memory.

    PubMed

    Dornelles, Arethuza; de Lima, Maria Noemia Martins; Grazziotin, Manoela; Presti-Torres, Juliana; Garcia, Vanessa Athaide; Scalco, Felipe Siciliani; Roesler, Rafael; Schröder, Nadja

    2007-07-01

    Extensive evidence indicates that epinephrine (EPI) modulates memory consolidation for emotionally arousing tasks in animals and human subjects. However, previous studies have not examined the effects of EPI on consolidation of recognition memory. Here we report that systemic administration of EPI enhances consolidation of memory for a novel object recognition (NOR) task under different training conditions. Control male rats given a systemic injection of saline (0.9% NaCl) immediately after NOR training showed significant memory retention when tested at 1.5 or 24, but not 96h after training. In contrast, rats given a post-training injection of EPI showed significant retention of NOR at all delays. In a second experiment using a different training condition, rats treated with EPI, but not SAL-treated animals, showed significant NOR retention at both 1.5 and 24-h delays. We next showed that the EPI-induced enhancement of retention tested at 96h after training was prevented by pretraining systemic administration of the beta-adrenoceptor antagonist propranolol. The findings suggest that, as previously observed in experiments using aversively motivated tasks, epinephrine modulates consolidation of recognition memory and that the effects require activation of beta-adrenoceptors.

  6. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

    PubMed Central

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-01-01

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

  7. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

    PubMed

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-06-10

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

  8. Aniracetam restores object recognition impaired by age, scopolamine, and nucleus basalis lesions.

    PubMed

    Bartolini, L; Casamenti, F; Pepeu, G

    1996-02-01

    Object recognition was investigated in adult and aging male rats in a two-trials, unrewarded, test that assessed a form of working-episodic memory. Exploration time in the first trial, in which two copies of the same object were presented, was recorded. In the second trial, in which one of the familiar objects and a new object were presented, the time spent exploring the two objects was separately recorded and a discrimination index was calculated. Adult rats explored the new object longer than the familiar object when the intertrial time ranged from 1 to 60 min. Rats older than 20 months of age did not discriminate between familiar and new objects. Object discrimination was lost in adult rats after scopolamine (0.2 mg/kg SC) administration and with lesions of the nucleus basalis, resulting in a 40% decrease in cortical ChAT activity. Both aniracetam (25, 50, 100 mg/kg os) and oxiracetam (50 mg/kg os) restored object recognition in aging rats, in rats treated with scopolamine, and with lesions of the nucleus basalis. In the rat, object discrimination appears to depend on the integrity of the cholinergic system, and nootropic drugs can correct its disruption.

  9. Neural network application for thermal image recognition of low-resolution objects

    NASA Astrophysics Data System (ADS)

    Fang, Yi-Chin; Wu, Bo-Wen

    2007-02-01

    In the ever-changing situation on a battle field, accurate recognition of a distant object is critical to a commander's decision-making and the general public's safety. Efficiently distinguishing between an enemy's armoured vehicles and ordinary civilian houses under all weather conditions has become an important research topic. This study presents a system for recognizing an armoured vehicle by distinguishing marks and contours. The characteristics of 12 different shapes and 12 characters are used to explore thermal image recognition under the circumstance of long distance and low resolution. Although the recognition capability of human eyes is superior to that of artificial intelligence under normal conditions, it tends to deteriorate substantially under long-distance and low-resolution scenarios. This study presents an effective method for choosing features and processing images. The artificial neural network technique is applied to further improve the probability of accurate recognition well beyond the limit of the recognition capability of human eyes.

  10. The Consolidation of Object and Context Recognition Memory Involve Different Regions of the Temporal Lobe

    ERIC Educational Resources Information Center

    Balderas, Israela; Rodriguez-Ortiz, Carlos J.; Salgado-Tonda, Paloma; Chavez-Hurtado, Julio; McGaugh, James L.; Bermudez-Rattoni, Federico

    2008-01-01

    These experiments investigated the involvement of several temporal lobe regions in consolidation of recognition memory. Anisomycin, a protein synthesis inhibitor, was infused into the hippocampus, perirhinal cortex, insular cortex, or basolateral amygdala of rats immediately after the sample phase of object or object-in-context recognition memory…

  11. Comparing object recognition from binary and bipolar edge images for visual prostheses.

    PubMed

    Jung, Jae-Hyun; Pu, Tian; Peli, Eli

    2016-11-01

    Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition.

  12. Comparing object recognition from binary and bipolar edge images for visual prostheses

    PubMed Central

    Jung, Jae-Hyun; Pu, Tian; Peli, Eli

    2017-01-01

    Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

  13. Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images.

    PubMed

    Udupa, Jayaram K; Odhner, Dewey; Zhao, Liming; Tong, Yubing; Matsumoto, Monica M S; Ciesielski, Krzysztof C; Falcao, Alexandre X; Vaideeswaran, Pavithra; Ciesielski, Victoria; Saboury, Babak; Mohammadianrasanani, Syedmehrdad; Sin, Sanghun; Arens, Raanan; Torigian, Drew A

    2014-07-01

    To make Quantitative Radiology (QR) a reality in radiological practice, computerized body-wide Automatic Anatomy Recognition (AAR) becomes essential. With the goal of building a general AAR system that is not tied to any specific organ system, body region, or image modality, this paper presents an AAR methodology for localizing and delineating all major organs in different body regions based on fuzzy modeling ideas and a tight integration of fuzzy models with an Iterative Relative Fuzzy Connectedness (IRFC) delineation algorithm. The methodology consists of five main steps: (a) gathering image data for both building models and testing the AAR algorithms from patient image sets existing in our health system; (b) formulating precise definitions of each body region and organ and delineating them following these definitions; (c) building hierarchical fuzzy anatomy models of organs for each body region; (d) recognizing and locating organs in given images by employing the hierarchical models; and (e) delineating the organs following the hierarchy. In Step (c), we explicitly encode object size and positional relationships into the hierarchy and subsequently exploit this information in object recognition in Step (d) and delineation in Step (e). Modality-independent and dependent aspects are carefully separated in model encoding. At the model building stage, a learning process is carried out for rehearsing an optimal threshold-based object recognition method. The recognition process in Step (d) starts from large, well-defined objects and proceeds down the hierarchy in a global to local manner. A fuzzy model-based version of the IRFC algorithm is created by naturally integrating the fuzzy model constraints into the delineation algorithm. The AAR system is tested on three body regions - thorax (on CT), abdomen (on CT and MRI), and neck (on MRI and CT) - involving a total of over 35 organs and 130 data sets (the total used for model building and testing). The training and

  14. Glucocorticoid effects on object recognition memory require training-associated emotional arousal.

    PubMed

    Okuda, Shoki; Roozendaal, Benno; McGaugh, James L

    2004-01-20

    Considerable evidence implicates glucocorticoid hormones in the regulation of memory consolidation and memory retrieval. The present experiments investigated whether the influence of these hormones on memory depends on the level of emotional arousal induced by the training experience. We investigated this issue in male Sprague-Dawley rats by examining the effects of immediate posttraining systemic injections of the glucocorticoid corticosterone on object recognition memory under two conditions that differed in their training-associated emotional arousal. In rats that were not previously habituated to the experimental context, corticosterone (0.3, 1.0, or 3.0 mg/kg, s.c.) administered immediately after a 3-min training trial enhanced 24-hr retention performance in an inverted-U shaped dose-response relationship. In contrast, corticosterone did not affect 24-hr retention of rats that received extensive prior habituation to the experimental context and, thus, had decreased novelty-induced emotional arousal during training. Additionally, immediate posttraining administration of corticosterone to nonhabituated rats, in doses that enhanced 24-hr retention, impaired object recognition performance at a 1-hr retention interval whereas corticosterone administered after training to well-habituated rats did not impair 1-hr retention. Thus, the present findings suggest that training-induced emotional arousal may be essential for glucocorticoid effects on object recognition memory.

  15. Deficits in object-in-place but not relative recency performance in the APPswe/PS1dE9 mouse model of Alzheimer's disease: Implications for object recognition.

    PubMed

    Bonardi, Charlotte; Pardon, Marie-Christine; Armstrong, Paul

    2016-10-15

    Performance was examined on three variants of the spontaneous object recognition (SOR) task, in 5-month old APPswe/PS1dE9 mice and wild-type littermate controls. A deficit was observed in an object-in-place (OIP) task, in which mice are preexposed to four different objects in specific locations, and then at test two of the objects swap locations (Experiment 2). Typically more exploration is seen of the objects which have switched location, which is taken as evidence of a retrieval-generated priming mechanism. However, no significant transgenic deficit was found in a relative recency (RR) task (Experiment 1), in which mice are exposed to two different objects in two separate sample phases, and then tested with both objects. Typically more exploration of the first-presented object is observed, which is taken as evidence of a self-generated priming mechanism. Nor was there any impairment in the simplest variant, the spontaneous object recognition (SOR) task, in which mice are preexposed to one object and then tested with the familiar and a novel object. This was true regardless of whether the sample-test interval was 5min (Experiment 1) or 24h (Experiments 1 and 2). It is argued that SOR performance depends on retrieval-generated priming as well as self-generated priming, and our preliminary evidence suggests that the retrieval-generated priming process is especially impaired in these young transgenic animals. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Using an Improved SIFT Algorithm and Fuzzy Closed-Loop Control Strategy for Object Recognition in Cluttered Scenes

    PubMed Central

    Nie, Haitao; Long, Kehui; Ma, Jun; Yue, Dan; Liu, Jinguo

    2015-01-01

    Partial occlusions, large pose variations, and extreme ambient illumination conditions generally cause the performance degradation of object recognition systems. Therefore, this paper presents a novel approach for fast and robust object recognition in cluttered scenes based on an improved scale invariant feature transform (SIFT) algorithm and a fuzzy closed-loop control method. First, a fast SIFT algorithm is proposed by classifying SIFT features into several clusters based on several attributes computed from the sub-orientation histogram (SOH), in the feature matching phase only features that share nearly the same corresponding attributes are compared. Second, a feature matching step is performed following a prioritized order based on the scale factor, which is calculated between the object image and the target object image, guaranteeing robust feature matching. Finally, a fuzzy closed-loop control strategy is applied to increase the accuracy of the object recognition and is essential for autonomous object manipulation process. Compared to the original SIFT algorithm for object recognition, the result of the proposed method shows that the number of SIFT features extracted from an object has a significant increase, and the computing speed of the object recognition processes increases by more than 40%. The experimental results confirmed that the proposed method performs effectively and accurately in cluttered scenes. PMID:25714094

  17. A knowledge-based object recognition system for applications in the space station

    NASA Technical Reports Server (NTRS)

    Dhawan, Atam P.

    1988-01-01

    A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

  18. How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

    PubMed

    Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

    2015-01-01

    The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Modelling of DNA-protein recognition

    NASA Technical Reports Server (NTRS)

    Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.

    1980-01-01

    Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.

  20. RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

    NASA Astrophysics Data System (ADS)

    El Bekri, Nadia; Angele, Susanne; Ruckhäberle, Martin; Peinsipp-Byma, Elisabeth; Haelke, Bruno

    2015-10-01

    This paper introduces an interactive recognition assistance system for imaging reconnaissance. This system supports aerial image analysts on missions during two main tasks: Object recognition and infrastructure analysis. Object recognition concentrates on the classification of one single object. Infrastructure analysis deals with the description of the components of an infrastructure and the recognition of the infrastructure type (e.g. military airfield). Based on satellite or aerial images, aerial image analysts are able to extract single object features and thereby recognize different object types. It is one of the most challenging tasks in the imaging reconnaissance. Currently, there are no high potential ATR (automatic target recognition) applications available, as consequence the human observer cannot be replaced entirely. State-of-the-art ATR applications cannot assume in equal measure human perception and interpretation. Why is this still such a critical issue? First, cluttered and noisy images make it difficult to automatically extract, classify and identify object types. Second, due to the changed warfare and the rise of asymmetric threats it is nearly impossible to create an underlying data set containing all features, objects or infrastructure types. Many other reasons like environmental parameters or aspect angles compound the application of ATR supplementary. Due to the lack of suitable ATR procedures, the human factor is still important and so far irreplaceable. In order to use the potential benefits of the human perception and computational methods in a synergistic way, both are unified in an interactive assistance system. RecceMan® (Reconnaissance Manual) offers two different modes for aerial image analysts on missions: the object recognition mode and the infrastructure analysis mode. The aim of the object recognition mode is to recognize a certain object type based on the object features that originated from the image signatures. The

  1. Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

    NASA Astrophysics Data System (ADS)

    Iqtait, M.; Mohamad, F. S.; Mamat, M.

    2018-03-01

    Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

  2. Environmental enrichment improves novel object recognition and enhances agonistic behavior in male mice.

    PubMed

    Mesa-Gresa, Patricia; Pérez-Martinez, Asunción; Redolat, Rosa

    2013-01-01

    Environmental enrichment (EE) is an experimental paradigm in which rodents are housed in complex environments containing objects that provide stimulation, the effects of which are expected to improve the welfare of these subjects. EE has been shown to considerably improve learning and memory in rodents. However, knowledge about the effects of EE on social interaction is generally limited and rather controversial. Thus, our aim was to evaluate both novel object recognition and agonistic behavior in NMRI mice receiving EE, hypothesizing enhanced cognition and slightly enhanced agonistic interaction upon EE rearing. During a 4-week period half the mice (n = 16) were exposed to EE and the other half (n = 16) remained in a standard environment (SE). On PND 56-57, animals performed the object recognition test, in which recognition memory was measured using a discrimination index. The social interaction test consisted of an encounter between an experimental animal and a standard opponent. Results indicated that EE mice explored the new object for longer periods than SE animals (P < .05). During social encounters, EE mice devoted more time to sociability and agonistic behavior (P < .05) than their non-EE counterparts. In conclusion, EE has been shown to improve object recognition and increase agonistic behavior in adolescent/early adulthood mice. In the future we intend to extend this study on a longitudinal basis in order to assess in more depth the effect of EE and the consistency of the above-mentioned observations in NMRI mice. Copyright © 2013 Wiley Periodicals, Inc.

  3. Representations of Shape in Object Recognition and Long-Term Visual Memory

    DTIC Science & Technology

    1993-02-11

    in anything other than linguistic terms ( Biederman , 1987 , for example). STATUS 1. Viewpoint-Dependent Features in Object Representation Tarr and...is object- based orientation-independent representations sufficient for "basic-level" categorization ( Biederman , 1987 ; Corballis, 1988). Alternatively...space. REFERENCES Biederman , I. ( 1987 ). Recognition-by-components: A theory of human image understanding. Psychological Review, 94,115-147. Cooper, L

  4. Multiple degree of freedom object recognition using optical relational graph decision nets

    NASA Technical Reports Server (NTRS)

    Casasent, David P.; Lee, Andrew J.

    1988-01-01

    Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

  5. Impaired recognition of faces and objects in dyslexia: Evidence for ventral stream dysfunction?

    PubMed

    Sigurdardottir, Heida Maria; Ívarsson, Eysteinn; Kristinsdóttir, Kristjana; Kristjánsson, Árni

    2015-09-01

    The objective of this study was to establish whether or not dyslexics are impaired at the recognition of faces and other complex nonword visual objects. This would be expected based on a meta-analysis revealing that children and adult dyslexics show functional abnormalities within the left fusiform gyrus, a brain region high up in the ventral visual stream, which is thought to support the recognition of words, faces, and other objects. 20 adult dyslexics (M = 29 years) and 20 matched typical readers (M = 29 years) participated in the study. One dyslexic-typical reader pair was excluded based on Adult Reading History Questionnaire scores and IS-FORM reading scores. Performance was measured on 3 high-level visual processing tasks: the Cambridge Face Memory Test, the Vanderbilt Holistic Face Processing Test, and the Vanderbilt Expertise Test. People with dyslexia are impaired in their recognition of faces and other visually complex objects. Their holistic processing of faces appears to be intact, suggesting that dyslexics may instead be specifically impaired at part-based processing of visual objects. The difficulty that people with dyslexia experience with reading might be the most salient manifestation of a more general high-level visual deficit. (c) 2015 APA, all rights reserved).

  6. Neural Representations that Support Invariant Object Recognition

    PubMed Central

    Goris, Robbe L. T.; Op de Beeck, Hans P.

    2008-01-01

    Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) ‘average’ neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously. PMID:19242556

  7. A rat in the sewer: How mental imagery interacts with object recognition

    PubMed Central

    Hamburger, Kai

    2018-01-01

    The role of mental imagery has been puzzling researchers for more than two millennia. Both positive and negative effects of mental imagery on information processing have been discussed. The aim of this work was to examine how mental imagery affects object recognition and associative learning. Based on different perceptual and cognitive accounts we tested our imagery-induced interaction hypothesis in a series of two experiments. According to that, mental imagery could lead to (1) a superior performance in object recognition and associative learning if these objects are imagery-congruent (semantically) and to (2) an inferior performance if these objects are imagery-incongruent. In the first experiment, we used a static environment and tested associative learning. In the second experiment, subjects encoded object information in a dynamic environment by means of a virtual sewer system. Our results demonstrate that subjects who received a role adoption task (by means of guided mental imagery) performed better when imagery-congruent objects were used and worse when imagery-incongruent objects were used. We finally discuss our findings also with respect to alternative accounts and plead for a multi-methodological approach for future research in order to solve this issue. PMID:29590161

  8. A rat in the sewer: How mental imagery interacts with object recognition.

    PubMed

    Karimpur, Harun; Hamburger, Kai

    2018-01-01

    The role of mental imagery has been puzzling researchers for more than two millennia. Both positive and negative effects of mental imagery on information processing have been discussed. The aim of this work was to examine how mental imagery affects object recognition and associative learning. Based on different perceptual and cognitive accounts we tested our imagery-induced interaction hypothesis in a series of two experiments. According to that, mental imagery could lead to (1) a superior performance in object recognition and associative learning if these objects are imagery-congruent (semantically) and to (2) an inferior performance if these objects are imagery-incongruent. In the first experiment, we used a static environment and tested associative learning. In the second experiment, subjects encoded object information in a dynamic environment by means of a virtual sewer system. Our results demonstrate that subjects who received a role adoption task (by means of guided mental imagery) performed better when imagery-congruent objects were used and worse when imagery-incongruent objects were used. We finally discuss our findings also with respect to alternative accounts and plead for a multi-methodological approach for future research in order to solve this issue.

  9. Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

    PubMed

    Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

    2017-06-21

    In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

  10. Reader error, object recognition, and visual search

    NASA Astrophysics Data System (ADS)

    Kundel, Harold L.

    2004-05-01

    Small abnormalities such as hairline fractures, lung nodules and breast tumors are missed by competent radiologists with sufficient frequency to make them a matter of concern to the medical community; not only because they lead to litigation but also because they delay patient care. It is very easy to attribute misses to incompetence or inattention. To do so may be placing an unjustified stigma on the radiologists involved and may allow other radiologists to continue a false optimism that it can never happen to them. This review presents some of the fundamentals of visual system function that are relevant to understanding the search for and the recognition of small targets embedded in complicated but meaningful backgrounds like chests and mammograms. It presents a model for visual search that postulates a pre-attentive global analysis of the retinal image followed by foveal checking fixations and eventually discovery scanning. The model will be used to differentiate errors of search, recognition and decision making. The implications for computer aided diagnosis and for functional workstation design are discussed.

  11. Complementary Hemispheric Asymmetries in Object Naming and Recognition: A Voxel-Based Correlational Study

    ERIC Educational Resources Information Center

    Acres, K.; Taylor, K. I.; Moss, H. E.; Stamatakis, E. A.; Tyler, L. K.

    2009-01-01

    Cognitive neuroscientific research proposes complementary hemispheric asymmetries in naming and recognising visual objects, with a left temporal lobe advantage for object naming and a right temporal lobe advantage for object recognition. Specifically, it has been proposed that the left inferior temporal lobe plays a mediational role linking…

  12. Face Recognition Is Affected by Similarity in Spatial Frequency Range to a Greater Degree Than Within-Category Object Recognition

    ERIC Educational Resources Information Center

    Collin, Charles A.; Liu, Chang Hong; Troje, Nikolaus F.; McMullen, Patricia A.; Chaudhuri, Avi

    2004-01-01

    Previous studies have suggested that face identification is more sensitive to variations in spatial frequency content than object recognition, but none have compared how sensitive the 2 processes are to variations in spatial frequency overlap (SFO). The authors tested face and object matching accuracy under varying SFO conditions. Their results…

  13. Viewpoint dependence in the recognition of non-elongated familiar objects: testing the effects of symmetry, front-back axis, and familiarity.

    PubMed

    Niimi, Ryosuke; Yokosawa, Kazuhiko

    2009-01-01

    Visual recognition of three-dimensional (3-D) objects is relatively impaired for some particular views, called accidental views. For most familiar objects, the front and top views are considered to be accidental views. Previous studies have shown that foreshortening of the axes of elongation of objects in these views impairs recognition, but the influence of other possible factors is largely unknown. Using familiar objects without a salient axis of elongation, we found that a foreshortened symmetry plane of the object and low familiarity of the viewpoint accounted for the relatively worse recognition for front views and top views, independently of the effect of a foreshortened axis of elongation. We found no evidence that foreshortened front-back axes impaired recognition in front views. These results suggest that the viewpoint dependence of familiar object recognition is not a unitary phenomenon. The possible role of symmetry (either 2-D or 3-D) in familiar object recognition is also discussed.

  14. Rotation And Scale Invariant Object Recognition Using A Distributed Associative Memory

    NASA Astrophysics Data System (ADS)

    Wechsler, Harry; Zimmerman, George Lee

    1988-04-01

    This paper describes an approach to 2-dimensional object recognition. Complex-log conformal mapping is combined with a distributed associative memory to create a system which recognizes objects regardless of changes in rotation or scale. Recalled information from the memorized database is used to classify an object, reconstruct the memorized version of the object, and estimate the magnitude of changes in scale or rotation. The system response is resistant to moderate amounts of noise and occlusion. Several experiments, using real, gray scale images, are presented to show the feasibility of our approach.

  15. Real-time optical multiple object recognition and tracking system and method

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin (Inventor); Liu, Hua Kuang (Inventor)

    1987-01-01

    The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

  16. Learning Distance Functions for Exemplar-Based Object Recognition

    DTIC Science & Technology

    2007-08-08

    requires prior specific permission. Learning Distance Functions for Exemplar-Based Object Recognition by Andrea Lynn Frome B.S. ( Mary Washington...fantastic advisor and advocate when I was at Mary Washington College i and has since become a dear friend. Thank you, Dr. Bass, for continuing to stand...Antonio Torralba. 5 Chapter 1. Introduction 0 5 10 15 20 25 30 35 10 15 20 25 30 35 40 45 50 55 60 65 70 Number of training examples per class M ea n

  17. Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

    PubMed

    Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

    2018-02-26

    The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

  18. Environmental modeling and recognition for an autonomous land vehicle

    NASA Technical Reports Server (NTRS)

    Lawton, D. T.; Levitt, T. S.; Mcconnell, C. C.; Nelson, P. C.

    1987-01-01

    An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perceptual structure database, the grouping processes that operate over this, schemas, and the long term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given.

  19. Target Recognition Using Neural Networks for Model Deformation Measurements

    NASA Technical Reports Server (NTRS)

    Ross, Richard W.; Hibler, David L.

    1999-01-01

    Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

  20. Visual object recognition for mobile tourist information systems

    NASA Astrophysics Data System (ADS)

    Paletta, Lucas; Fritz, Gerald; Seifert, Christin; Luley, Patrick; Almer, Alexander

    2005-03-01

    We describe a mobile vision system that is capable of automated object identification using images captured from a PDA or a camera phone. We present a solution for the enabling technology of outdoors vision based object recognition that will extend state-of-the-art location and context aware services towards object based awareness in urban environments. In the proposed application scenario, tourist pedestrians are equipped with GPS, W-LAN and a camera attached to a PDA or a camera phone. They are interested whether their field of view contains tourist sights that would point to more detailed information. Multimedia type data about related history, the architecture, or other related cultural context of historic or artistic relevance might be explored by a mobile user who is intending to learn within the urban environment. Learning from ambient cues is in this way achieved by pointing the device towards the urban sight, capturing an image, and consequently getting information about the object on site and within the focus of attention, i.e., the users current field of view.

  1. Learning Distance Functions for Exemplar-Based Object Recognition

    DTIC Science & Technology

    2007-01-01

    Learning Distance Functions for Exemplar-Based Object Recognition by Andrea Lynn Frome B.S. ( Mary Washington College) 1996 A dissertation submitted...advisor and advocate when I was at Mary Washington College i and has since become a dear friend. Thank you, Dr. Bass, for continuing to stand by my...Torralba. 5 Chapter 1. Introduction 0 5 10 15 20 25 30 35 10 15 20 25 30 35 40 45 50 55 60 65 70 Number of training examples per class M ea n re co

  2. Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

    PubMed

    O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

    2015-09-01

    Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

  3. The Dynamic Multisensory Engram: Neural Circuitry Underlying Crossmodal Object Recognition in Rats Changes with the Nature of Object Experience.

    PubMed

    Jacklin, Derek L; Cloke, Jacob M; Potvin, Alphonse; Garrett, Inara; Winters, Boyer D

    2016-01-27

    Rats, humans, and monkeys demonstrate robust crossmodal object recognition (CMOR), identifying objects across sensory modalities. We have shown that rats' performance of a spontaneous tactile-to-visual CMOR task requires functional integration of perirhinal (PRh) and posterior parietal (PPC) cortices, which seemingly provide visual and tactile object feature processing, respectively. However, research with primates has suggested that PRh is sufficient for multisensory object representation. We tested this hypothesis in rats using a modification of the CMOR task in which multimodal preexposure to the to-be-remembered objects significantly facilitates performance. In the original CMOR task, with no preexposure, reversible lesions of PRh or PPC produced patterns of impairment consistent with modality-specific contributions. Conversely, in the CMOR task with preexposure, PPC lesions had no effect, whereas PRh involvement was robust, proving necessary for phases of the task that did not require PRh activity when rats did not have preexposure; this pattern was supported by results from c-fos imaging. We suggest that multimodal preexposure alters the circuitry responsible for object recognition, in this case obviating the need for PPC contributions and expanding PRh involvement, consistent with the polymodal nature of PRh connections and results from primates indicating a key role for PRh in multisensory object representation. These findings have significant implications for our understanding of multisensory information processing, suggesting that the nature of an individual's past experience with an object strongly determines the brain circuitry involved in representing that object's multisensory features in memory. The ability to integrate information from multiple sensory modalities is crucial to the survival of organisms living in complex environments. Appropriate responses to behaviorally relevant objects are informed by integration of multisensory object features

  4. Dopamine D1 receptor stimulation modulates the formation and retrieval of novel object recognition memory: Role of the prelimbic cortex

    PubMed Central

    Pezze, Marie A.; Marshall, Hayley J.; Fone, Kevin C.F.; Cassaday, Helen J.

    2015-01-01

    Previous studies have shown that dopamine D1 receptor antagonists impair novel object recognition memory but the effects of dopamine D1 receptor stimulation remain to be determined. This study investigated the effects of the selective dopamine D1 receptor agonist SKF81297 on acquisition and retrieval in the novel object recognition task in male Wistar rats. SKF81297 (0.4 and 0.8 mg/kg s.c.) given 15 min before the sampling phase impaired novel object recognition evaluated 10 min or 24 h later. The same treatments also reduced novel object recognition memory tested 24 h after the sampling phase and when given 15 min before the choice session. These data indicate that D1 receptor stimulation modulates both the encoding and retrieval of object recognition memory. Microinfusion of SKF81297 (0.025 or 0.05 μg/side) into the prelimbic sub-region of the medial prefrontal cortex (mPFC) in this case 10 min before the sampling phase also impaired novel object recognition memory, suggesting that the mPFC is one important site mediating the effects of D1 receptor stimulation on visual recognition memory. PMID:26277743

  5. Image object recognition based on the Zernike moment and neural networks

    NASA Astrophysics Data System (ADS)

    Wan, Jianwei; Wang, Ling; Huang, Fukan; Zhou, Liangzhu

    1998-03-01

    This paper first give a comprehensive discussion about the concept of artificial neural network its research methods and the relations with information processing. On the basis of such a discussion, we expound the mathematical similarity of artificial neural network and information processing. Then, the paper presents a new method of image recognition based on invariant features and neural network by using image Zernike transform. The method not only has the invariant properties for rotation, shift and scale of image object, but also has good fault tolerance and robustness. Meanwhile, it is also compared with statistical classifier and invariant moments recognition method.

  6. Exploring local regularities for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Tian, Huaiwen; Qin, Shengfeng

    2016-11-01

    In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness.

  7. How landmark suitability shapes recognition memory signals for objects in the medial temporal lobes.

    PubMed

    Martin, Chris B; Sullivan, Jacqueline A; Wright, Jessey; Köhler, Stefan

    2018-02-01

    A role of perirhinal cortex (PrC) in recognition memory for objects has been well established. Contributions of parahippocampal cortex (PhC) to this function, while documented, remain less well understood. Here, we used fMRI to examine whether the organization of item-based recognition memory signals across these two structures is shaped by object category, independent of any difference in representing episodic context. Guided by research suggesting that PhC plays a critical role in processing landmarks, we focused on three categories of objects that differ from each other in their landmark suitability as confirmed with behavioral ratings (buildings > trees > aircraft). Participants made item-based recognition-memory decisions for novel and previously studied objects from these categories, which were matched in accuracy. Multi-voxel pattern classification revealed category-specific item-recognition memory signals along the long axis of PrC and PhC, with no sharp functional boundaries between these structures. Memory signals for buildings were observed in the mid to posterior extent of PhC, signals for trees in anterior to posterior segments of PhC, and signals for aircraft in mid to posterior aspects of PrC and the anterior extent of PhC. Notably, item-based memory signals for the category with highest landmark suitability ratings were observed only in those posterior segments of PhC that also allowed for classification of landmark suitability of objects when memory status was held constant. These findings provide new evidence in support of the notion that item-based memory signals for objects are not limited to PrC, and that the organization of these signals along the longitudinal axis that crosses PrC and PhC can be captured with reference to landmark suitability. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Reversibility of object recognition but not spatial memory impairment following binge-like alcohol exposure in rats

    PubMed Central

    Cippitelli, Andrea; Zook, Michelle; Bell, Lauren; Damadzic, Ruslan; Eskay, Robert L.; Schwandt, Melanie; Heilig, Markus

    2010-01-01

    Excessive alcohol use leads to neurodegeneration in several brain structures including the hippocampal dentate gyrus and the entorhinal cortex. Cognitive deficits that result are among the most insidious and debilitating consequences of alcoholism. The object exploration task (OET) provides a sensitive measurement of spatial memory impairment induced by hippocampal and cortical damage. In this study, we examine whether the observed neurotoxicity produced by a 4-day binge ethanol treatment results in long-term memory impairment by observing the time course of reactions to spatial change (object configuration) and non-spatial change (object recognition). Wistar rats were assessed for their abilities to detect spatial configuration in the OET at 1 week and 10 weeks following the ethanol treatment, in which ethanol groups received 9–15 g/kg/day and achieved blood alcohol levels over 300 mg/dl. At 1 week, results indicated that the binge alcohol treatment produced impairment in both spatial memory and non-spatial object recognition performance. Unlike the controls, ethanol treated rats did not increase the duration or number of contacts with the displaced object in the spatial memory task, nor did they increase the duration of contacts with the novel object in the object recognition task. After 10 weeks, spatial memory remained impaired in the ethanol treated rats but object recognition ability was recovered. Our data suggest that episodes of binge-like alcohol exposure result in long-term and possibly permanent impairments in memory for the configuration of objects during exploration, whereas the ability to detect non-spatial changes is only temporarily affected. PMID:20849966

  9. Dynamic information processing states revealed through neurocognitive models of object semantics

    PubMed Central

    Clarke, Alex

    2015-01-01

    Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

  10. [Recognition of visual objects under forward masking. Effects of cathegorial similarity of test and masking stimuli].

    PubMed

    Gerasimenko, N Iu; Slavutskaia, A V; Kalinin, S A; Kulikov, M A; Mikhaĭlova, E S

    2013-01-01

    In 38 healthy subjects accuracy and response time were examined during recognition of two categories of images--animals andnonliving objects--under forward masking. We revealed new data that masking effects depended of categorical similarity of target and masking stimuli. The recognition accuracy was the lowest and the response time was the most slow, when the target and masking stimuli belongs to the same category, that was combined with high dispersion of response times. The revealed effects were more clear in the task of animal recognition in comparison with the recognition of nonliving objects. We supposed that the revealed effects connected with interference between cortical representations of the target and masking stimuli and discussed our results in context of cortical interference and negative priming.

  11. A fast 3-D object recognition algorithm for the vision system of a special-purpose dexterous manipulator

    NASA Technical Reports Server (NTRS)

    Hung, Stephen H. Y.

    1989-01-01

    A fast 3-D object recognition algorithm that can be used as a quick-look subsystem to the vision system for the Special-Purpose Dexterous Manipulator (SPDM) is described. Global features that can be easily computed from range data are used to characterize the images of a viewer-centered model of an object. This algorithm will speed up the processing by eliminating the low level processing whenever possible. It may identify the object, reject a set of bad data in the early stage, or create a better environment for a more powerful algorithm to carry the work further.

  12. Circular blurred shape model for multiclass symbol recognition.

    PubMed

    Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia

    2011-04-01

    In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.

  13. Novel object recognition ability in female mice following exposure to nanoparticle-rich diesel exhaust

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Win-Shwe, Tin-Tin, E-mail: tin.tin.win.shwe@nies.go.jp; Fujimaki, Hidekazu; Fujitani, Yuji

    2012-08-01

    Recently, our laboratory reported that exposure to nanoparticle-rich diesel exhaust (NRDE) for 3 months impaired hippocampus-dependent spatial learning ability and up-regulated the expressions of memory function-related genes in the hippocampus of female mice. However, whether NRDE affects the hippocampus-dependent non-spatial learning ability and the mechanism of NRDE-induced neurotoxicity was unknown. Female BALB/c mice were exposed to clean air, middle-dose NRDE (M-NRDE, 47 μg/m{sup 3}), high-dose NRDE (H-NRDE, 129 μg/m{sup 3}), or filtered H-NRDE (F-DE) for 3 months. We then investigated the effect of NRDE exposure on non-spatial learning ability and the expression of genes related to glutamate neurotransmission using amore » novel object recognition test and a real-time RT-PCR analysis, respectively. We also examined microglia marker Iba1 immunoreactivity in the hippocampus using immunohistochemical analyses. Mice exposed to H-NRDE or F-DE could not discriminate between familiar and novel objects. The control and M-NRDE-exposed groups showed a significantly increased discrimination index, compared to the H-NRDE-exposed group. Although no significant changes in the expression levels of the NMDA receptor subunits were observed, the expression of glutamate transporter EAAT4 was decreased and that of glutamic acid decarboxylase GAD65 was increased in the hippocampus of H-NRDE-exposed mice, compared with the expression levels in control mice. We also found that microglia activation was prominent in the hippocampal area of the H-NRDE-exposed mice, compared with the other groups. These results indicated that exposure to NRDE for 3 months impaired the novel object recognition ability. The present study suggests that genes related to glutamate metabolism may be involved in the NRDE-induced neurotoxicity observed in the present mouse model. -- Highlights: ► The effects of nanoparticle-induced neurotoxicity remain unclear. ► We investigated the effect of exposure

  14. Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

    PubMed

    Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

    2009-02-01

    Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

  15. Tactile agnosia. Underlying impairment and implications for normal tactile object recognition.

    PubMed

    Reed, C L; Caselli, R J; Farah, M J

    1996-06-01

    In a series of experimental investigations of a subject with a unilateral impairment of tactile object recognition without impaired tactile sensation, several issues were addressed. First, is tactile agnosia secondary to a general impairment of spatial cognition? On tests of spatial ability, including those directed at the same spatial integration process assumed to be taxed by tactile object recognition, the subject performed well, implying a more specific impairment of high level, modality specific tactile perception. Secondly, within the realm of high level tactile perception, is there a distinction between the ability to derive shape ('what') and spatial ('where') information? Our testing showed an impairment confined to shape perception. Thirdly, what aspects of shape perception are impaired in tactile agnosia? Our results indicate that despite accurate encoding of metric length and normal manual exploration strategies, the ability tactually to perceive objects with the impaired hand, deteriorated as the complexity of shape increased. In addition, asymmetrical performance was not found for other body surfaces (e.g. her feet). Our results suggest that tactile shape perception can be disrupted independent of general spatial ability, tactile spatial ability, manual shape exploration, or even the precise perception of metric length in the tactile modality.

  16. BDNF Expression in Perirhinal Cortex is Associated with Exercise-Induced Improvement in Object Recognition Memory

    PubMed Central

    Hopkins, Michael E.; Bucci, David J.

    2010-01-01

    Physical exercise induces widespread neurobiological adaptations and improves learning and memory. Most research in this field has focused on hippocampus-based spatial tasks and changes in brain-derived neurotrophic factor (BDNF) as a putative substrate underlying exercise-induced cognitive improvements. Chronic exercise can also be anxiolytic and causes adaptive changes in stress reactivity. The present study employed a perirhinal cortex-dependent object recognition task as well as the elevated plus maze to directly test for interactions between the cognitive and anxiolytic effects of exercise in male Long Evans rats. Hippocampal and perirhinal cortex tissue was collected to determine whether the relationship between BDNF and cognitive performance extends to this non-spatial and non-hippocampal-dependent task. We also examined whether the cognitive improvements persisted once the exercise regimen was terminated. Our data indicate that 4 weeks of voluntary exercise every-other-day improved object recognition memory. Importantly, BDNF expression in the perirhinal cortex of exercising rats was strongly correlated with object recognition memory. Exercise also decreased anxiety-like behavior, however there was no evidence to support a relationship between anxiety-like behavior and performance on the novel object recognition task. There was a trend for a negative relationship between anxiety-like behavior and hippocampal BDNF. Neither the cognitive improvements nor the relationship between cognitive function and perirhinal BDNF levels persisted after 2 weeks of inactivity. These are the first data demonstrating that region-specific changes in BDNF protein levels are correlated with exercise-induced improvements in non-spatial memory, mediated by structures outside the hippocampus and are consistent with the theory that, with regard to object recognition, the anxiolytic and cognitive effects of exercise may be mediated through separable mechanisms. PMID:20601027

  17. Reversibility of object recognition but not spatial memory impairment following binge-like alcohol exposure in rats.

    PubMed

    Cippitelli, Andrea; Zook, Michelle; Bell, Lauren; Damadzic, Ruslan; Eskay, Robert L; Schwandt, Melanie; Heilig, Markus

    2010-11-01

    Excessive alcohol use leads to neurodegeneration in several brain structures including the hippocampal dentate gyrus and the entorhinal cortex. Cognitive deficits that result are among the most insidious and debilitating consequences of alcoholism. The object exploration task (OET) provides a sensitive measurement of spatial memory impairment induced by hippocampal and cortical damage. In this study, we examine whether the observed neurotoxicity produced by a 4-day binge ethanol treatment results in long-term memory impairment by observing the time course of reactions to spatial change (object configuration) and non-spatial change (object recognition). Wistar rats were assessed for their abilities to detect spatial configuration in the OET at 1 week and 10 weeks following the ethanol treatment, in which ethanol groups received 9-15 g/kg/day and achieved blood alcohol levels over 300 mg/dl. At 1 week, results indicated that the binge alcohol treatment produced impairment in both spatial memory and non-spatial object recognition performance. Unlike the controls, ethanol treated rats did not increase the duration or number of contacts with the displaced object in the spatial memory task, nor did they increase the duration of contacts with the novel object in the object recognition task. After 10 weeks, spatial memory remained impaired in the ethanol treated rats but object recognition ability was recovered. Our data suggest that episodes of binge-like alcohol exposure result in long-term and possibly permanent impairments in memory for the configuration of objects during exploration, whereas the ability to detect non-spatial changes is only temporarily affected. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

    PubMed

    Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

    2017-10-01

    Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Automatic anatomy recognition on CT images with pathology

    NASA Astrophysics Data System (ADS)

    Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

    2016-03-01

    Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

  20. Chronic cannabidiol treatment improves social and object recognition in double transgenic APPswe/PS1∆E9 mice.

    PubMed

    Cheng, David; Low, Jac Kee; Logge, Warren; Garner, Brett; Karl, Tim

    2014-08-01

    Patients suffering from Alzheimer's disease (AD) exhibit a decline in cognitive abilities including an inability to recognise familiar faces. Hallmark pathological changes in AD include the aggregation of amyloid-β (Aβ), tau protein hyperphosphorylation as well as pronounced neurodegeneration, neuroinflammation, neurotoxicity and oxidative damage. The non-psychoactive phytocannabinoid cannabidiol (CBD) exerts neuroprotective, anti-oxidant and anti-inflammatory effects and promotes neurogenesis. CBD also reverses Aβ-induced spatial memory deficits in rodents. Thus we determined the therapeutic-like effects of chronic CBD treatment (20 mg/kg, daily intraperitoneal injections for 3 weeks) on the APPswe/PS1∆E9 (APPxPS1) transgenic mouse model for AD in a number of cognitive tests, including the social preference test, the novel object recognition task and the fear conditioning paradigm. We also analysed the impact of CBD on anxiety behaviours in the elevated plus maze. Vehicle-treated APPxPS1 mice demonstrated impairments in social recognition and novel object recognition compared to wild type-like mice. Chronic CBD treatment reversed these cognitive deficits in APPxPS1 mice without affecting anxiety-related behaviours. This is the first study to investigate the effect of chronic CBD treatment on cognition in an AD transgenic mouse model. Our findings suggest that CBD may have therapeutic potential for specific cognitive impairments associated with AD.

  1. Developmental Trajectories of Part-Based and Configural Object Recognition in Adolescence

    ERIC Educational Resources Information Center

    Juttner, Martin; Wakui, Elley; Petters, Dean; Kaur, Surinder; Davidoff, Jules

    2013-01-01

    Three experiments assessed the development of children's part and configural (part-relational) processing in object recognition during adolescence. In total, 312 school children aged 7-16 years and 80 adults were tested in 3-alternative forced choice (3-AFC) tasks. They judged the correct appearance of upright and inverted presented familiar…

  2. Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

    NASA Astrophysics Data System (ADS)

    Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

    2017-12-01

    The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

  3. Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

    NASA Astrophysics Data System (ADS)

    Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

    2006-05-01

    Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

  4. Crowded and sparse domains in object recognition: consequences for categorization and naming.

    PubMed

    Gale, Tim M; Laws, Keith R; Foley, Kerry

    2006-03-01

    Some models of object recognition propose that items from structurally crowded categories (e.g., living things) permit faster access to superordinate semantic information than structurally dissimilar categories (e.g., nonliving things), but slower access to individual object information when naming items. We present four experiments that utilize the same matched stimuli: two examine superordinate categorization and two examine picture naming. Experiments 1 and 2 required participants to sort pictures into their appropriate superordinate categories and both revealed faster categorization for living than nonliving things. Nonetheless, the living thing superiority disappeared when the atypical categories of body parts and musical instruments were excluded. Experiment 3 examined naming latency and found no difference between living and nonliving things. This finding was replicated in Experiment 4 where the same items were presented in different formats (e.g., color and line-drawn versions). Taken as a whole, these experiments show that the ease with which people categorize items maps strongly onto the ease with which they name them.

  5. Real-Time pedestrian detection : layered object recognition system for pedestrian collision sensing.

    DOT National Transportation Integrated Search

    2010-01-01

    In 2005 alone, 64,000 pedestrians were injured and 4,882 were killed in the United States, with pedestrians accounting for 11 percent of all traffic fatalities and 2 percent of injuries. The focus of "Layered Object Recognition System for Pedestrian ...

  6. The Role of Sensory-Motor Information in Object Recognition: Evidence from Category-Specific Visual Agnosia

    ERIC Educational Resources Information Center

    Wolk, D.A.; Coslett, H.B.; Glosser, G.

    2005-01-01

    The role of sensory-motor representations in object recognition was investigated in experiments involving AD, a patient with mild visual agnosia who was impaired in the recognition of visually presented living as compared to non-living entities. AD named visually presented items for which sensory-motor information was available significantly more…

  7. Somatostatin Signaling in Neuronal Cilia Is Criticalfor Object Recognition Memory

    PubMed Central

    Einstein, Emily B.; Patterson, Carlyn A.; Hon, Beverly J.; Regan, Kathleen A.; Reddi, Jyoti; Melnikoff, David E.; Mateer, Marcus J.; Schulz, Stefan; Johnson, Brian N.

    2010-01-01

    Most neurons possess a single, nonmotile cilium that projects out from the cell surface. These microtubule-based organelles are important in brain development and neurogenesis; however, their function in mature neurons is unknown. Cilia express a complement of proteins distinct from other neuronal compartments, one of which is the somatostatin receptor subtype SST3. We show here that SST3 is critical for object recognition memory in mice. sst3 knock-out mice are severely impaired in discriminating novel objects, whereas they retain normal memory for object location. Further, systemic injection of an SST3 antagonist (ACQ090) disrupts recall of familiar objects in wild-type mice. To examine mechanisms of SST3, we tested synaptic plasticity in CA1 hippocampus. Electrically evoked long-term potentiation (LTP) was normal in sst3 knock-out mice, while adenylyl cyclase/cAMP-mediated LTP was impaired. The SST3 antagonist also disrupted cAMP-mediated LTP. Basal cAMP levels in hippocampal lysate were reduced in sst3 knock-out mice compared with wild-type mice, while the forskolin-induced increase in cAMP levels was normal. The SST3 antagonist inhibited forskolin-stimulated cAMP increases, whereas the SST3 agonist L-796,778 increased basal cAMP levels in hippocampal slices but not hippocampal lysate. Our results show that somatostatin signaling in neuronal cilia is critical for recognition memory and suggest that the cAMP pathway is a conserved signaling motif in cilia. Neuronal cilia therefore represent a novel nonsynaptic compartment crucial for signaling involved in a specific form of synaptic plasticity and in novelty detection. PMID:20335466

  8. Knowledge-based object recognition for different morphological classes of plants

    NASA Astrophysics Data System (ADS)

    Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.; Megnet, Roland

    1995-01-01

    Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic syshoot. In this paper we describe parts of the vision syshoot that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, shoot, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods. As a result of our work we present rules which help users to create specific algorithms for object recognition of plant species.

  9. Face Memory and Object Recognition in Children with High-Functioning Autism or Asperger Syndrome and in Their Parents

    ERIC Educational Resources Information Center

    Kuusikko-Gauffin, Sanna; Jansson-Verkasalo, Eira; Carter, Alice; Pollock-Wurman, Rachel; Jussila, Katja; Mattila, Marja-Leena; Rahko, Jukka; Ebeling, Hanna; Pauls, David; Moilanen, Irma

    2011-01-01

    Children with Autism Spectrum Disorders (ASDs) have reported to have impairments in face, recognition and face memory, but intact object recognition and object memory. Potential abnormalities, in these fields at the family level of high-functioning children with ASD remains understudied despite, the ever-mounting evidence that ASDs are genetic and…

  10. People's Risk Recognition Preceding Evacuation and Its Role in Demand Modeling and Planning.

    PubMed

    Urata, Junji; Pel, Adam J

    2018-05-01

    Evacuation planning and management involves estimating the travel demand in the event that such action is required. This is usually done as a function of people's decision to evacuate, which we show is strongly linked to their risk awareness. We use an empirical data set, which shows tsunami evacuation behavior, to demonstrate that risk recognition is not synonymous with objective risk, but is instead determined by a combination of factors including risk education, information, and sociodemographics, and that it changes dynamically over time. Based on these findings, we formulate an ordered logit model to describe risk recognition combined with a latent class model to describe evacuation choices. Our proposed evacuation choice model along with a risk recognition class can evaluate quantitatively the influence of disaster mitigation measures, risk education, and risk information. The results obtained from the risk recognition model show that risk information has a greater impact in the sense that people recognize their high risk. The results of the evacuation choice model show that people who are unaware of their risk take a longer time to evacuate. © 2017 Society for Risk Analysis.

  11. Neuropeptide Trefoil factor 3 improves learning and retention of novel object recognition memory in mice.

    PubMed

    Shi, Hai-Shui; Yin, Xi; Song, Li; Guo, Qing-Jun; Luo, Xiang-Heng

    2012-02-01

    Accumulating evidence has implicated neuropeptides in modulating recognition, learning and memory. However, to date, no study has investigated the effects of neuropeptide Trefoil factor 3 (TFF3) on the process of learning and memory. In the present study, we evaluated the acute effects of TFF3 administration (0.1 and 0.5mg/kg, i.p.) on the acquisition and retention of object recognition memory in mice. We found that TFF3 administration significantly enhanced both short-term and long-term memory during the retention test, conducted 90 min and 24h after training respectively. Remarkably, acute TFF3 administration transformed a learning event that would not normally result in long-term memory into an event retained for a long-term period and produced no effect on locomotor activity in mice. In conclusion, the present results provide an important role of TFF3 in improving object recognition memory and reserving it for a longer time, which suggests a potential therapeutic application for diseases with recognition and memory impairment. Copyright © 2011 Elsevier B.V. All rights reserved.

  12. [Influence of object material and inter-trial interval on novel object recognition test in mice].

    PubMed

    Li, Sheng-jian; Huang, Zhu-yan; Ye, Yi-lu; Yu, Yue-ping; Zhang, Wei-ping; Wei, Er-qing; Zhang, Qi

    2014-05-01

    To investigate the efficacy of novel object recognition (NOR) test in assessment of learning and memory ability in ICR mice in different experimental conditions. One hundred and thirty male ICR mice were randomly divided into 10 groups: 4 groups for different inter-trial intervals (ITI: 10 min, 90 min, 4 h, 24 h), 4 groups for different object materials (wood-wood, plastic-plastic, plastic-wood, wood-plastic) and 2 groups for repeated test (measured once a day or every 3 days, totally three times in each group). The locomotor tracks in the open field were recorded. The amount of time spent exploring the novel and familiar objects, the discrimination ratio (DR) and the discrimination index (DI) were analyzed. Compared with familiar object, DR and DI of novel object were both increased at ITI of 10 min and 90 min (P<0.01). Exploring time, DR and DI were greatly influenced by different object materials. DR and DI remained stable by using identical object material. NOR test could be done repeatedly in the same batch of mice. NOR test can be used to assess the learning and memory ability in mice at shorter ITI and with identical material. It can be done repeatedly.

  13. Mice deficient for striatal Vesicular Acetylcholine Transporter (VAChT) display impaired short-term but normal long-term object recognition memory.

    PubMed

    Palmer, Daniel; Creighton, Samantha; Prado, Vania F; Prado, Marco A M; Choleris, Elena; Winters, Boyer D

    2016-09-15

    Substantial evidence implicates Acetylcholine (ACh) in the acquisition of object memories. While most research has focused on the role of the cholinergic basal forebrain and its cortical targets, there are additional cholinergic networks that may contribute to object recognition. The striatum contains an independent cholinergic network comprised of interneurons. In the current study, we investigated the role of this cholinergic signalling in object recognition using mice deficient for Vesicular Acetylcholine Transporter (VAChT) within interneurons of the striatum. We tested whether these striatal VAChT(D2-Cre-flox/flox) mice would display normal short-term (5 or 15min retention delay) and long-term (3h retention delay) object recognition memory. In a home cage object recognition task, male and female VAChT(D2-Cre-flox/flox) mice were impaired selectively with a 15min retention delay. When tested on an object location task, VAChT(D2-Cre-flox/flox) mice displayed intact spatial memory. Finally, when object recognition was tested in a Y-shaped apparatus, designed to minimize the influence of spatial and contextual cues, only females displayed impaired recognition with a 5min retention delay, but when males were challenged with a 15min retention delay, they were also impaired; neither males nor females were impaired with the 3h delay. The pattern of results suggests that striatal cholinergic transmission plays a role in the short-term memory for object features, but not spatial location. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. The Role of Fixation and Visual Attention in Object Recognition.

    DTIC Science & Technology

    1995-01-01

    computers", Technical Report, Aritificial Intelligence Lab, M.I. T., AI-Memo-915, June 1986. [29] D.P. Huttenlocher and S.Ullman, "Object Recognition Using...attention", Technical Report, Aritificial Intelligence Lab, M.I. T., AI-memo-770, Jan 1984. [35] E.Krotkov, K. Henriksen and R. Kories, "Stereo...MIT Artificial Intelligence Laboratory [ PCTBTBimON STATEMENT X \\ Afipioved tor puciic reieo*«* \\ »?*•;.., jDi*tiibutK» U»lisut»d* 19951004

  15. Endomorphin-1 attenuates Aβ42 induced impairment of novel object and object location recognition tasks in mice.

    PubMed

    Zhang, Rui-san; Xu, Hong-jiao; Jiang, Jin-hong; Han, Ren-wen; Chang, Min; Peng, Ya-li; Wang, Yuan; Wang, Rui

    2015-12-10

    A growing body of evidence suggests that the agglomeration of amyloid-β (Aβ) may be a trigger for Alzheimer׳s disease (AD). Central infusion of Aβ42 can lead to memory impairment in mice. Inhibiting the aggregation of Aβ has been considered a therapeutic strategy for AD. Endomorphin-1 (EM-1), an endogenous agonist of μ-opioid receptors, has been shown to inhibit the aggregation of Aβ in vitro. In the present study, we investigated whether EM-1 could alleviate the memory-impairing effects of Aβ42 in mice using novel object recognition (NOR) and object location recognition (OLR) tasks. We showed that co-administration of EM-1 was able to ameliorate Aβ42-induced amnesia in the lateral ventricle and the hippocampus, and these effects could not be inhibited by naloxone, an antagonist of μ-opioid receptors. Infusion of EM-1 or naloxone separately into the lateral ventricle had no influence on memory in the tasks. These results suggested that EM-1 might be effective as a drug for AD preventative treatment by inhibiting Aβ aggregation directly as a molecular modifier. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    PubMed

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  17. Conversion of short-term to long-term memory in the novel object recognition paradigm.

    PubMed

    Moore, Shannon J; Deshpande, Kaivalya; Stinnett, Gwen S; Seasholtz, Audrey F; Murphy, Geoffrey G

    2013-10-01

    It is well-known that stress can significantly impact learning; however, whether this effect facilitates or impairs the resultant memory depends on the characteristics of the stressor. Investigation of these dynamics can be confounded by the role of the stressor in motivating performance in a task. Positing a cohesive model of the effect of stress on learning and memory necessitates elucidating the consequences of stressful stimuli independently from task-specific functions. Therefore, the goal of this study was to examine the effect of manipulating a task-independent stressor (elevated light level) on short-term and long-term memory in the novel object recognition paradigm. Short-term memory was elicited in both low light and high light conditions, but long-term memory specifically required high light conditions during the acquisition phase (familiarization trial) and was independent of the light level during retrieval (test trial). Additionally, long-term memory appeared to be independent of stress-mediated glucocorticoid release, as both low and high light produced similar levels of plasma corticosterone, which further did not correlate with subsequent memory performance. Finally, both short-term and long-term memory showed no savings between repeated experiments suggesting that this novel object recognition paradigm may be useful for longitudinal studies, particularly when investigating treatments to stabilize or enhance weak memories in neurodegenerative diseases or during age-related cognitive decline. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Conversion of short-term to long-term memory in the novel object recognition paradigm

    PubMed Central

    Moore, Shannon J.; Deshpande, Kaivalya; Stinnett, Gwen S.; Seasholtz, Audrey F.; Murphy, Geoffrey G.

    2013-01-01

    It is well-known that stress can significantly impact learning; however, whether this effect facilitates or impairs the resultant memory depends on the characteristics of the stressor. Investigation of these dynamics can be confounded by the role of the stressor in motivating performance in a task. Positing a cohesive model of the effect of stress on learning and memory necessitates elucidating the consequences of stressful stimuli independently from task-specific functions. Therefore, the goal of this study was to examine the effect of manipulating a task-independent stressor (elevated light level) on short-term and long-term memory in the novel object recognition paradigm. Short-term memory was elicited in both low light and high light conditions, but long-term memory specifically required high light conditions during the acquisition phase (familiarization trial) and was independent of the light level during retrieval (test trial). Additionally, long-term memory appeared to be independent of stress-mediated glucocorticoid release, as both low and high light produced similar levels of plasma corticosterone, which further did not correlate with subsequent memory performance. Finally, both short-term and long-term memory showed no savings between repeated experiments suggesting that this novel object recognition paradigm may be useful for longitudinal studies, particularly when investigating treatments to stabilize or enhance weak memories in neurodegenerative diseases or during age-related cognitive decline. PMID:23835143

  19. Marked Object Recognition Multitouch Screen Printed Touchpad for Interactive Applications

    PubMed Central

    Nunes, Jivago Serrado; Castro, Nelson; Pereira, Nélson; Correia, Vitor; Lanceros-Mendez, Senentxu

    2017-01-01

    The market for interactive platforms is rapidly growing, and touchscreens have been incorporated in an increasing number of devices. Thus, the area of smart objects and devices is strongly increasing by adding interactive touch and multimedia content, leading to new uses and capabilities. In this work, a flexible screen printed sensor matrix is fabricated based on silver ink in a polyethylene terephthalate (PET) substrate. Diamond shaped capacitive electrodes coupled with conventional capacitive reading electronics enables fabrication of a highly functional capacitive touchpad, and also allows for the identification of marked objects. For the latter, the capacitive signatures are identified by intersecting points and distances between them. Thus, this work demonstrates the applicability of a low cost method using royalty-free geometries and technologies for the development of flexible multitouch touchpads for the implementation of interactive and object recognition applications. PMID:29194414

  20. Marked Object Recognition Multitouch Screen Printed Touchpad for Interactive Applications.

    PubMed

    Nunes, Jivago Serrado; Castro, Nelson; Gonçalves, Sergio; Pereira, Nélson; Correia, Vitor; Lanceros-Mendez, Senentxu

    2017-12-01

    The market for interactive platforms is rapidly growing, and touchscreens have been incorporated in an increasing number of devices. Thus, the area of smart objects and devices is strongly increasing by adding interactive touch and multimedia content, leading to new uses and capabilities. In this work, a flexible screen printed sensor matrix is fabricated based on silver ink in a polyethylene terephthalate (PET) substrate. Diamond shaped capacitive electrodes coupled with conventional capacitive reading electronics enables fabrication of a highly functional capacitive touchpad, and also allows for the identification of marked objects. For the latter, the capacitive signatures are identified by intersecting points and distances between them. Thus, this work demonstrates the applicability of a low cost method using royalty-free geometries and technologies for the development of flexible multitouch touchpads for the implementation of interactive and object recognition applications.

  1. Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition

    PubMed Central

    Kheradpisheh, Saeed Reza; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

    2016-01-01

    Deep convolutional neural networks (DCNNs) have attracted much attention recently, and have shown to be able to recognize thousands of object categories in natural image databases. Their architecture is somewhat similar to that of the human visual system: both use restricted receptive fields, and a hierarchy of layers which progressively extract more and more abstracted features. Yet it is unknown whether DCNNs match human performance at the task of view-invariant object recognition, whether they make similar errors and use similar representations for this task, and whether the answers depend on the magnitude of the viewpoint variations. To investigate these issues, we benchmarked eight state-of-the-art DCNNs, the HMAX model, and a baseline shallow model and compared their results to those of humans with backward masking. Unlike in all previous DCNN studies, we carefully controlled the magnitude of the viewpoint variations to demonstrate that shallow nets can outperform deep nets and humans when variations are weak. When facing larger variations, however, more layers were needed to match human performance and error distributions, and to have representations that are consistent with human behavior. A very deep net with 18 layers even outperformed humans at the highest variation level, using the most human-like representations. PMID:27601096

  2. Operator for object recognition and scene analysis by estimation of set occupancy with noisy and incomplete data sets

    NASA Astrophysics Data System (ADS)

    Rees, S. J.; Jones, Bryan F.

    1992-11-01

    Once feature extraction has occurred in a processed image, the recognition problem becomes one of defining a set of features which maps sufficiently well onto one of the defined shape/object models to permit a claimed recognition. This process is usually handled by aggregating features until a large enough weighting is obtained to claim membership, or an adequate number of located features are matched to the reference set. A requirement has existed for an operator or measure capable of a more direct assessment of membership/occupancy between feature sets, particularly where the feature sets may be defective representations. Such feature set errors may be caused by noise, by overlapping of objects, and by partial obscuration of features. These problems occur at the point of acquisition: repairing the data would then assume a priori knowledge of the solution. The technique described in this paper offers a set theoretical measure for partial occupancy defined in terms of the set of minimum additions to permit full occupancy and the set of locations of occupancy if such additions are made. As is shown, this technique permits recognition of partial feature sets with quantifiable degrees of uncertainty. A solution to the problems of obscuration and overlapping is therefore available.

  3. Invariant object recognition based on the generalized discrete radon transform

    NASA Astrophysics Data System (ADS)

    Easley, Glenn R.; Colonna, Flavia

    2004-04-01

    We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

  4. Object-oriented recognition of high-resolution remote sensing image

    NASA Astrophysics Data System (ADS)

    Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

    2016-01-01

    With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

  5. Hidden Markov models for character recognition.

    PubMed

    Vlontzos, J A; Kung, S Y

    1992-01-01

    A hierarchical system for character recognition with hidden Markov model knowledge sources which solve both the context sensitivity problem and the character instantiation problem is presented. The system achieves 97-99% accuracy using a two-level architecture and has been implemented using a systolic array, thus permitting real-time (1 ms per character) multifont and multisize printed character recognition as well as handwriting recognition.

  6. Effects of heavy particle irradiation and diet on object recognition memory in rats

    NASA Astrophysics Data System (ADS)

    Rabin, Bernard M.; Carrihill-Knoll, Kirsty; Hinchman, Marie; Shukitt-Hale, Barbara; Joseph, James A.; Foster, Brian C.

    2009-04-01

    On long-duration missions to other planets astronauts will be exposed to types and doses of radiation that are not experienced in low earth orbit. Previous research using a ground-based model for exposure to cosmic rays has shown that exposure to heavy particles, such as 56Fe, disrupts spatial learning and memory measured using the Morris water maze. Maintaining rats on diets containing antioxidant phytochemicals for 2 weeks prior to irradiation ameliorated this deficit. The present experiments were designed to determine: (1) the generality of the particle-induced disruption of memory by examining the effects of exposure to 56Fe particles on object recognition memory; and (2) whether maintaining rats on these antioxidant diets for 2 weeks prior to irradiation would also ameliorate any potential deficit. The results showed that exposure to low doses of 56Fe particles does disrupt recognition memory and that maintaining rats on antioxidant diets containing blueberry and strawberry extract for only 2 weeks was effective in ameliorating the disruptive effects of irradiation. The results are discussed in terms of the mechanisms by which exposure to these particles may produce effects on neurocognitive performance.

  7. Long-lasting effects of prenatal dietary choline availability on object recognition memory ability in adult rats.

    PubMed

    Moreno, Hayarelis C; de Brugada, Isabel; Carias, Diamela; Gallo, Milagros

    2013-11-01

    Choline is an essential nutrient required for early development. Previous studies have shown that prenatal choline availability influences adult memory abilities depending on the medial temporal lobe integrity. The relevance of prenatal choline availability on object recognition memory was assessed in adult Wistar rats. Three groups of pregnant Wistar rats were fed from E12 to E18 with choline-deficient (0 g/kg choline chloride), standard (1.1 g/kg choline chloride), or choline-supplemented (5 g/kg choline chloride) diets. The offspring was cross-fostered to rat dams fed a standard diet during pregnancy and tested at the age of 3 months in an object recognition memory task applying retention tests 24 and 48 hours after acquisition. Although no significant differences have been found in the performance of the three groups during the first retention test, the supplemented group exhibited improved memory compared with both the standard and the deficient group in the second retention test, 48 hours after acquisition. In addition, at the second retention test the deficient group did not differ from chance. Taken together, the results support the notion of a long-lasting beneficial effect of prenatal choline supplementation on object recognition memory which is evident when the rats reach adulthood. The results are discussed in terms of their relevance for improving the understanding of the cholinergic involvement in object recognition memory and the implications of the importance of maternal diet for lifelong cognitive abilities.

  8. Effect of a Bluetooth-implemented hearing aid on speech recognition performance: subjective and objective measurement.

    PubMed

    Kim, Min-Beom; Chung, Won-Ho; Choi, Jeesun; Hong, Sung Hwa; Cho, Yang-Sun; Park, Gyuseok; Lee, Sangmin

    2014-06-01

    The object was to evaluate speech perception improvement through Bluetooth-implemented hearing aids in hearing-impaired adults. Thirty subjects with bilateral symmetric moderate sensorineural hearing loss participated in this study. A Bluetooth-implemented hearing aid was fitted unilaterally in all study subjects. Objective speech recognition score and subjective satisfaction were measured with a Bluetooth-implemented hearing aid to replace the acoustic connection from either a cellular phone or a loudspeaker system. In each system, participants were assigned to 4 conditions: wireless speech signal transmission into hearing aid (wireless mode) in quiet or noisy environment and conventional speech signal transmission using external microphone of hearing aid (conventional mode) in quiet or noisy environment. Also, participants completed questionnaires to investigate subjective satisfaction. Both cellular phone and loudspeaker system situation, participants showed improvements in sentence and word recognition scores with wireless mode compared to conventional mode in both quiet and noise conditions (P < .001). Participants also reported subjective improvements, including better sound quality, less noise interference, and better accuracy naturalness, when using the wireless mode (P < .001). Bluetooth-implemented hearing aids helped to improve subjective and objective speech recognition performances in quiet and noisy environments during the use of electronic audio devices.

  9. A multistream model of visual word recognition.

    PubMed

    Allen, Philip A; Smith, Albert F; Lien, Mei-Ching; Kaut, Kevin P; Canfield, Angie

    2009-02-01

    Four experiments are reported that test a multistream model of visual word recognition, which associates letter-level and word-level processing channels with three known visual processing streams isolated in macaque monkeys: the magno-dominated (MD) stream, the interblob-dominated (ID) stream, and the blob-dominated (BD) stream (Van Essen & Anderson, 1995). We show that mixing the color of adjacent letters of words does not result in facilitation of response times or error rates when the spatial-frequency pattern of a whole word is familiar. However, facilitation does occur when the spatial-frequency pattern of a whole word is not familiar. This pattern of results is not due to different luminance levels across the different-colored stimuli and the background because isoluminant displays were used. Also, the mixed-case, mixed-hue facilitation occurred when different display distances were used (Experiments 2 and 3), so this suggests that image normalization can adjust independently of object size differences. Finally, we show that this effect persists in both spaced and unspaced conditions (Experiment 4)--suggesting that inappropriate letter grouping by hue cannot account for these results. These data support a model of visual word recognition in which lower spatial frequencies are processed first in the more rapid MD stream. The slower ID and BD streams may process some lower spatial frequency information in addition to processing higher spatial frequency information, but these channels tend to lose the processing race to recognition unless the letter string is unfamiliar to the MD stream--as with mixed-case presentation.

  10. An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

    USGS Publications Warehouse

    Maddox, Brian G.; Swadley, Casey L.

    2002-01-01

    Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

  11. Multispectral image analysis for object recognition and classification

    NASA Astrophysics Data System (ADS)

    Viau, C. R.; Payeur, P.; Cretu, A.-M.

    2016-05-01

    Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

  12. HONTIOR - HIGHER-ORDER NEURAL NETWORK FOR TRANSFORMATION INVARIANT OBJECT RECOGNITION

    NASA Technical Reports Server (NTRS)

    Spirkovska, L.

    1994-01-01

    Neural networks have been applied in numerous fields, including transformation invariant object recognition, wherein an object is recognized despite changes in the object's position in the input field, size, or rotation. One of the more successful neural network methods used in invariant object recognition is the higher-order neural network (HONN) method. With a HONN, known relationships are exploited and the desired invariances are built directly into the architecture of the network, eliminating the need for the network to learn invariance to transformations. This results in a significant reduction in the training time required, since the network needs to be trained on only one view of each object, not on numerous transformed views. Moreover, one hundred percent accuracy is guaranteed for images characterized by the built-in distortions, providing noise is not introduced through pixelation. The program HONTIOR implements a third-order neural network having invariance to translation, scale, and in-plane rotation built directly into the architecture, Thus, for 2-D transformation invariance, the network needs only to be trained on just one view of each object. HONTIOR can also be used for 3-D transformation invariant object recognition by training the network only on a set of out-of-plane rotated views. Historically, the major drawback of HONNs has been that the size of the input field was limited to the memory required for the large number of interconnections in a fully connected network. HONTIOR solves this problem by coarse coding the input images (coding an image as a set of overlapping but offset coarser images). Using this scheme, large input fields (4096 x 4096 pixels) can easily be represented using very little virtual memory (30Mb). The HONTIOR distribution consists of three main programs. The first program contains the training and testing routines for a third-order neural network. The second program contains the same training and testing procedures as the

  13. Selective attention affects conceptual object priming and recognition: a study with young and older adults.

    PubMed

    Ballesteros, Soledad; Mayas, Julia

    2014-01-01

    In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old-new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/artificial speeded conceptual classification task with repeated attended, repeated unattended, and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classify them as natural or artificial. After the encoding phase, they performed an old-new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults.

  14. Selective attention affects conceptual object priming and recognition: a study with young and older adults

    PubMed Central

    Ballesteros, Soledad; Mayas, Julia

    2015-01-01

    In the present study, we investigated the effects of selective attention at encoding on conceptual object priming (Experiment 1) and old–new recognition memory (Experiment 2) tasks in young and older adults. The procedures of both experiments included encoding and memory test phases separated by a short delay. At encoding, the picture outlines of two familiar objects, one in blue and the other in green, were presented to the left and to the right of fixation. In Experiment 1, participants were instructed to attend to the picture outline of a certain color and to classify the object as natural or artificial. After a short delay, participants performed a natural/artificial speeded conceptual classification task with repeated attended, repeated unattended, and new pictures. In Experiment 2, participants at encoding memorized the attended pictures and classify them as natural or artificial. After the encoding phase, they performed an old–new recognition memory task. Consistent with previous findings with perceptual priming tasks, we found that conceptual object priming, like explicit memory, required attention at encoding. Significant priming was obtained in both age groups, but only for those pictures that were attended at encoding. Although older adults were slower than young adults, both groups showed facilitation for attended pictures. In line with previous studies, young adults had better recognition memory than older adults. PMID:25628588

  15. Intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory.

    PubMed

    Takeda, Atsushi; Tamano, Haruna; Ogawa, Taisuke; Takada, Shunsuke; Nakamura, Masatoshi; Fujii, Hiroaki; Ando, Masaki

    2014-11-01

    The role of perforant pathway-dentate granule cell synapses in cognitive behavior was examined focusing on synaptic Zn(2+) signaling in the dentate gyrus. Object recognition memory was transiently impaired when extracellular Zn(2+) levels were decreased by injection of clioquinol and N,N,N',N'-tetrakis-(2-pyridylmethyl) ethylendediamine. To pursue the effect of the loss and/or blockade of Zn(2+) signaling in dentate granule cells, ZnAF-2DA (100 pmol, 0.1 mM/1 µl), an intracellular Zn(2+) chelator, was locally injected into the dentate molecular layer of rats. ZnAF-2DA injection, which was estimated to chelate intracellular Zn(2+) signaling only in the dentate gyrus, affected object recognition memory 1 h after training without affecting intracellular Ca(2+) signaling in the dentate molecular layer. In vivo dentate gyrus long-term potentiation (LTP) was affected under the local perfusion of the recording region (the dentate granule cell layer) with 0.1 mM ZnAF-2DA, but not with 1-10 mM CaEDTA, an extracellular Zn(2+) chelator, suggesting that the blockade of intracellular Zn(2+) signaling in dentate granule cells affects dentate gyrus LTP. The present study demonstrates that intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory, probably via dentate gyrus LTP expression. Copyright © 2014 Wiley Periodicals, Inc.

  16. Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

    NASA Astrophysics Data System (ADS)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

    2009-08-01

    Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

  17. A PDP model of the simultaneous perception of multiple objects

    NASA Astrophysics Data System (ADS)

    Henderson, Cynthia M.; McClelland, James L.

    2011-06-01

    Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

  18. Describing, using 'recognition cones'. [parallel-series model with English-like computer program

    NASA Technical Reports Server (NTRS)

    Uhr, L.

    1973-01-01

    A parallel-serial 'recognition cone' model is examined, taking into account the model's ability to describe scenes of objects. An actual program is presented in an English-like language. The concept of a 'description' is discussed together with possible types of descriptive information. Questions regarding the level and the variety of detail are considered along with approaches for improving the serial representations of parallel systems.

  19. Multiscale moment-based technique for object matching and recognition

    NASA Astrophysics Data System (ADS)

    Thio, HweeLi; Chen, Liya; Teoh, Eam-Khwang

    2000-03-01

    A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

  20. Biased figure-ground assignment affects conscious object recognition in spatial neglect.

    PubMed

    Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

    2010-09-01

    Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.

  1. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

    PubMed Central

    Rolls, Edmund T.

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

  2. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

    PubMed

    Rolls, Edmund T

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

  3. A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing

    PubMed Central

    Long, Chengjiang; Hua, Gang; Kapoor, Ashish

    2015-01-01

    We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892

  4. EMG-based speech recognition using hidden markov models with global control variables.

    PubMed

    Lee, Ki-Seung

    2008-03-01

    It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

  5. Shape and texture fused recognition of flying targets

    NASA Astrophysics Data System (ADS)

    Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

    2011-06-01

    This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

  6. Estradiol enhances object recognition memory in Swiss female mice by activating hippocampal estrogen receptor α.

    PubMed

    Pereira, Luciana M; Bastos, Cristiane P; de Souza, Jéssica M; Ribeiro, Fabíola M; Pereira, Grace S

    2014-10-01

    In rodents, 17β-estradiol (E2) enhances hippocampal function and improves performance in several memory tasks. Regarding the object recognition paradigm, E2 commonly act as a cognitive enhancer. However, the types of estrogen receptor (ER) involved, as well as the underlying molecular mechanisms are still under investigation. In the present study, we asked whether E2 enhances object recognition memory by activating ERα and/or ERβ in the hippocampus of Swiss female mice. First, we showed that immediately post-training intraperitoneal (i.p.) injection of E2 (0.2 mg/kg) allowed object recognition memory to persist 48 h in ovariectomized (OVX) Swiss female mice. This result indicates that Swiss female mice are sensitive to the promnesic effects of E2 and is in accordance with other studies, which used C57/BL6 female mice. To verify if the activation of hippocampal ERα or ERβ would be sufficient to improve object memory, we used PPT and DPN, which are selective ERα and ERβ agonists, respectively. We found that PPT, but not DPN, improved object memory in Swiss female mice. However, DPN was able to improve memory in C57/BL6 female mice, which is in accordance with other studies. Next, we tested if the E2 effect on improving object memory depends on ER activation in the hippocampus. Thus, we tested if the infusion of intra-hippocampal TPBM and PHTPP, selective antagonists of ERα and ERβ, respectively, would block the memory enhancement effect of E2. Our results showed that TPBM, but not PHTPP, blunted the promnesic effect of E2, strongly suggesting that in Swiss female mice, the ERα and not the ERβ is the receptor involved in the promnesic effect of E2. It was already demonstrated that E2, as well as PPT and DPN, increase the phospho-ERK2 level in the dorsal hippocampus of C57/BL6 mice. Here we observed that PPT increased phospho-ERK1, while DPN decreased phospho-ERK2 in the dorsal hippocampus of Swiss female mice subjected to the object recognition sample phase

  7. Short- and long-term effects of nicotine and the histone deacetylase inhibitor phenylbutyrate on novel object recognition in zebrafish.

    PubMed

    Faillace, M P; Pisera-Fuster, A; Medrano, M P; Bejarano, A C; Bernabeu, R O

    2017-03-01

    Zebrafish have a sophisticated color- and shape-sensitive visual system, so we examined color cue-based novel object recognition in zebrafish. We evaluated preference in the absence or presence of drugs that affect attention and memory retention in rodents: nicotine and the histone deacetylase inhibitor (HDACi) phenylbutyrate (PhB). The objective of this study was to evaluate whether nicotine and PhB affect innate preferences of zebrafish for familiar and novel objects after short- and long-retention intervals. We developed modified object recognition (OR) tasks using neutral novel and familiar objects in different colors. We also tested objects which differed with respect to the exploratory behavior they elicited from naïve zebrafish. Zebrafish showed an innate preference for exploring red or green objects rather than yellow or blue objects. Zebrafish were better at discriminating color changes than changes in object shape or size. Nicotine significantly enhanced or changed short-term innate novel object preference whereas PhB had similar effects when preference was assessed 24 h after training. Analysis of other zebrafish behaviors corroborated these results. Zebrafish were innately reluctant or prone to explore colored novel objects, so drug effects on innate preference for objects can be evaluated changing the color of objects with a simple geometry. Zebrafish exhibited recognition memory for novel objects with similar innate significance. Interestingly, nicotine and PhB significantly modified innate object preference.

  8. Tc1 mouse model of trisomy-21 dissociates properties of short- and long-term recognition memory.

    PubMed

    Hall, Jessica H; Wiseman, Frances K; Fisher, Elizabeth M C; Tybulewicz, Victor L J; Harwood, John L; Good, Mark A

    2016-04-01

    The present study examined memory function in Tc1 mice, a transchromosomic model of Down syndrome (DS). Tc1 mice demonstrated an unusual delay-dependent deficit in recognition memory. More specifically, Tc1 mice showed intact immediate (30sec), impaired short-term (10-min) and intact long-term (24-h) memory for objects. A similar pattern was observed for olfactory stimuli, confirming the generality of the pattern across sensory modalities. The specificity of the behavioural deficits in Tc1 mice was confirmed using APP overexpressing mice that showed the opposite pattern of object memory deficits. In contrast to object memory, Tc1 mice showed no deficit in either immediate or long-term memory for object-in-place information. Similarly, Tc1 mice showed no deficit in short-term memory for object-location information. The latter result indicates that Tc1 mice were able to detect and react to spatial novelty at the same delay interval that was sensitive to an object novelty recognition impairment. These results demonstrate (1) that novelty detection per se and (2) the encoding of visuo-spatial information was not disrupted in adult Tc1 mice. The authors conclude that the task specific nature of the short-term recognition memory deficit suggests that the trisomy of genes on human chromosome 21 in Tc1 mice impacts on (perirhinal) cortical systems supporting short-term object and olfactory recognition memory. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

    NASA Astrophysics Data System (ADS)

    Kuvich, Gary

    2004-08-01

    Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

  10. A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

    PubMed Central

    Balduzzi, David; Tononi, Giulio

    2012-01-01

    In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips. PMID:22615855

  11. Developmental Changes in Visual Object Recognition between 18 and 24 Months of Age

    ERIC Educational Resources Information Center

    Pereira, Alfredo F.; Smith, Linda B.

    2009-01-01

    Two experiments examined developmental changes in children's visual recognition of common objects during the period of 18 to 24 months. Experiment 1 examined children's ability to recognize common category instances that presented three different kinds of information: (1) richly detailed and prototypical instances that presented both local and…

  12. Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery

    PubMed Central

    Roldan, Stephanie M.

    2017-01-01

    One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation. PMID:28588538

  13. Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery.

    PubMed

    Roldan, Stephanie M

    2017-01-01

    One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation.

  14. Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

    PubMed

    Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

    2002-01-01

    The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can

  15. Modeling Spoken Word Recognition Performance by Pediatric Cochlear Implant Users using Feature Identification

    PubMed Central

    Frisch, Stefan A.; Pisoni, David B.

    2012-01-01

    Objective Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with

  16. Biological object recognition in μ-radiography images

    NASA Astrophysics Data System (ADS)

    Prochazka, A.; Dammer, J.; Weyda, F.; Sopko, V.; Benes, J.; Zeman, J.; Jandejsek, I.

    2015-03-01

    This study presents an applicability of real-time microradiography to biological objects, namely to horse chestnut leafminer, Cameraria ohridella (Insecta: Lepidoptera, Gracillariidae) and following image processing focusing on image segmentation and object recognition. The microradiography of insects (such as horse chestnut leafminer) provides a non-invasive imaging that leaves the organisms alive. The imaging requires a high spatial resolution (micrometer scale) radiographic system. Our radiographic system consists of a micro-focus X-ray tube and two types of detectors. The first is a charge integrating detector (Hamamatsu flat panel), the second is a pixel semiconductor detector (Medipix2 detector). The latter allows detection of single quantum photon of ionizing radiation. We obtained numerous horse chestnuts leafminer pupae in several microradiography images easy recognizable in automatic mode using the image processing methods. We implemented an algorithm that is able to count a number of dead and alive pupae in images. The algorithm was based on two methods: 1) noise reduction using mathematical morphology filters, 2) Canny edge detection. The accuracy of the algorithm is higher for the Medipix2 (average recall for detection of alive pupae =0.99, average recall for detection of dead pupae =0.83), than for the flat panel (average recall for detection of alive pupae =0.99, average recall for detection of dead pupae =0.77). Therefore, we conclude that Medipix2 has lower noise and better displays contours (edges) of biological objects. Our method allows automatic selection and calculation of dead and alive chestnut leafminer pupae. It leads to faster monitoring of the population of one of the world's important insect pest.

  17. Learning Models and Real-Time Speech Recognition.

    ERIC Educational Resources Information Center

    Danforth, Douglas G.; And Others

    This report describes the construction and testing of two "psychological" learning models for the purpose of computer recognition of human speech over the telephone. One of the two models was found to be superior in all tests. A regression analysis yielded a 92.3% recognition rate for 14 subjects ranging in age from 6 to 13 years. Tests…

  18. Better Object Recognition and Naming Outcome With MRI-Guided Stereotactic Laser Amygdalohippocampotomy for Temporal Lobe Epilepsy

    PubMed Central

    Drane, Daniel L.; Loring, David W.; Voets, Natalie L.; Price, Michele; Ojemann, Jeffrey G.; Willie, Jon T.; Saindane, Amit M.; Phatak, Vaishali; Ivanisevic, Mirjana; Millis, Scott; Helmers, Sandra L.; Miller, John W.; Meador, Kimford J.; Gross, Robert E.

    2015-01-01

    SUMMARY OBJECTIVES Temporal lobe epilepsy (TLE) patients experience significant deficits in category-related object recognition and naming following standard surgical approaches. These deficits may result from a decoupling of core processing modules (e.g., language, visual processing, semantic memory), due to “collateral damage” to temporal regions outside the hippocampus following open surgical approaches. We predicted stereotactic laser amygdalohippocampotomy (SLAH) would minimize such deficits because it preserves white matter pathways and neocortical regions critical for these cognitive processes. METHODS Tests of naming and recognition of common nouns (Boston Naming Test) and famous persons were compared with nonparametric analyses using exact tests between a group of nineteen patients with medically-intractable mesial TLE undergoing SLAH (10 dominant, 9 nondominant), and a comparable series of TLE patients undergoing standard surgical approaches (n=39) using a prospective, non-randomized, non-blinded, parallel group design. RESULTS Performance declines were significantly greater for the dominant TLE patients undergoing open resection versus SLAH for naming famous faces and common nouns (F=24.3, p<.0001, η2=.57, & F=11.2, p<.001, η2=.39, respectively), and for the nondominant TLE patients undergoing open resection versus SLAH for recognizing famous faces (F=3.9, p<.02, η2=.19). When examined on an individual subject basis, no SLAH patients experienced any performance declines on these measures. In contrast, 32 of the 39 undergoing standard surgical approaches declined on one or more measures for both object types (p<.001, Fisher’s exact test). Twenty-one of 22 left (dominant) TLE patients declined on one or both naming tasks after open resection, while 11 of 17 right (non-dominant) TLE patients declined on face recognition. SIGNIFICANCE Preliminary results suggest 1) naming and recognition functions can be spared in TLE patients undergoing SLAH, and 2

  19. Implicit Shape Models for Object Detection in 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Velizhev, A.; Shapovalov, R.; Schindler, K.

    2012-07-01

    We present a method for automatic object localization and recognition in 3D point clouds representing outdoor urban scenes. The method is based on the implicit shape models (ISM) framework, which recognizes objects by voting for their center locations. It requires only few training examples per class, which is an important property for practical use. We also introduce and evaluate an improved version of the spin image descriptor, more robust to point density variation and uncertainty in normal direction estimation. Our experiments reveal a significant impact of these modifications on the recognition performance. We compare our results against the state-of-the-art method and get significant improvement in both precision and recall on the Ohio dataset, consisting of combined aerial and terrestrial LiDAR scans of 150,000 m2 of urban area in total.

  20. Differential Roles for "Nr4a1" and "Nr4a2" in Object Location vs. Object Recognition Long-Term Memory

    ERIC Educational Resources Information Center

    McNulty, Susan E.; Barrett, Ruth M.; Vogel-Ciernia, Annie; Malvaez, Melissa; Hernandez, Nicole; Davatolhagh, M. Felicia; Matheos, Dina P.; Schiffman, Aaron; Wood, Marcelo A.

    2012-01-01

    "Nr4a1" and "Nr4a2" are transcription factors and immediate early genes belonging to the nuclear receptor Nr4a family. In this study, we examine their role in long-term memory formation for object location and object recognition. Using siRNA to block expression of either "Nr4a1" or "Nr4a2", we found that "Nr4a2" is necessary for both long-term…

  1. Perirhinal Cortex Resolves Feature Ambiguity in Configural Object Recognition and Perceptual Oddity Tasks

    ERIC Educational Resources Information Center

    Bartko, Susan J.; Winters, Boyer D.; Cowell, Rosemary A.; Saksida, Lisa M.; Bussey, Timothy J.

    2007-01-01

    The perirhinal cortex (PRh) has a well-established role in object recognition memory. More recent studies suggest that PRh is also important for two-choice visual discrimination tasks. Specifically, it has been suggested that PRh contains conjunctive representations that help resolve feature ambiguity, which occurs when a task cannot easily be…

  2. Coarse-coded higher-order neural networks for PSRI object recognition. [position, scale, and rotation invariant

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly; Reid, Max B.

    1993-01-01

    A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.

  3. Short-term blueberry-enriched antioxidant diet prevents and reverses object recognition memory loss in aged rats

    USDA-ARS?s Scientific Manuscript database

    Objective Previously, four months of a blueberry-enriched (BB) antioxidant diet prevented impaired object recognition memory in aged rats. Experiment 1 determined whether one and two-month BB diets would have a similar effect and whether the benefits would disappear promptly after terminating the d...

  4. Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

    PubMed

    Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

    2016-03-01

    In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats

  5. The medial prefrontal cortex-lateral entorhinal cortex circuit is essential for episodic-like memory and associative object-recognition.

    PubMed

    Chao, Owen Y; Huston, Joseph P; Li, Jay-Shake; Wang, An-Li; de Souza Silva, Maria A

    2016-05-01

    The prefrontal cortex directly projects to the lateral entorhinal cortex (LEC), an important substrate for engaging item-associated information and relaying the information to the hippocampus. Here we ask to what extent the communication between the prefrontal cortex and LEC is critically involved in the processing of episodic-like memory. We applied a disconnection procedure to test whether the interaction between the medial prefrontal cortex (mPFC) and LEC is essential for the expression of recognition memory. It was found that male rats that received unilateral NMDA lesions of the mPFC and LEC in the same hemisphere, exhibited intact episodic-like (what-where-when) and object-recognition memories. When these lesions were placed in the opposite hemispheres (disconnection), episodic-like and associative memories for object identity, location and context were impaired. However, the disconnection did not impair the components of episodic memory, namely memory for novel object (what), object place (where) and temporal order (when), per se. Thus, the present findings suggest that the mPFC and LEC are a critical part of a neural circuit that underlies episodic-like and associative object-recognition memory. © 2015 Wiley Periodicals, Inc.

  6. New neural-networks-based 3D object recognition system

    NASA Astrophysics Data System (ADS)

    Abolmaesumi, Purang; Jahed, M.

    1997-09-01

    Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

  7. Recognition of Simple 3D Geometrical Objects under Partial Occlusion

    NASA Astrophysics Data System (ADS)

    Barchunova, Alexandra; Sommer, Gerald

    In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

  8. Syntactic error modeling and scoring normalization in speech recognition

    NASA Technical Reports Server (NTRS)

    Olorenshaw, Lex

    1991-01-01

    The objective was to develop the speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Research was performed in the following areas: (1) syntactic error modeling; (2) score normalization; and (3) phoneme error modeling. The study into the types of errors that a reader makes will provide the basis for creating tests which will approximate the use of the system in the real world. NASA-Johnson will develop this technology into a 'Literacy Tutor' in order to bring innovative concepts to the task of teaching adults to read.

  9. Localized contourlet features in vehicle make and model recognition

    NASA Astrophysics Data System (ADS)

    Zafar, I.; Edirisinghe, E. A.; Acar, B. S.

    2009-02-01

    Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic Number Plate Recognition (ANPR) systems. Several vehicle MMR systems have been proposed in literature. In parallel to this, the usefulness of multi-resolution based feature analysis techniques leading to efficient object classification algorithms have received close attention from the research community. To this effect, Contourlet transforms that can provide an efficient directional multi-resolution image representation has recently been introduced. Already an attempt has been made in literature to use Curvelet/Contourlet transforms in vehicle MMR. In this paper we propose a novel localized feature detection method in Contourlet transform domain that is capable of increasing the classification rates up to 4%, as compared to the previously proposed Contourlet based vehicle MMR approach in which the features are non-localized and thus results in sub-optimal classification. Further we show that the proposed algorithm can achieve the increased classification accuracy of 96% at significantly lower computational complexity due to the use of Two Dimensional Linear Discriminant Analysis (2DLDA) for dimensionality reduction by preserving the features with high between-class variance and low inter-class variance.

  10. Recognition vs Reverse Engineering in Boolean Concepts Learning

    ERIC Educational Resources Information Center

    Shafat, Gabriel; Levin, Ilya

    2012-01-01

    This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

  11. Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition.

    PubMed

    Janko, Vito; Luštrek, Mitja

    2017-12-29

    The recognition of the user's context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system's energy expenditure and the system's accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.

  12. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

    PubMed

    Schädler, Marc R; Warzybok, Anna; Kollmeier, Birger

    2018-01-01

    The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

  13. The effect of scene context on episodic object recognition: parahippocampal cortex mediates memory encoding and retrieval success.

    PubMed

    Hayes, Scott M; Nadel, Lynn; Ryan, Lee

    2007-01-01

    Previous research has investigated intentional retrieval of contextual information and contextual influences on object identification and word recognition, yet few studies have investigated context effects in episodic memory for objects. To address this issue, unique objects embedded in a visually rich scene or on a white background were presented to participants. At test, objects were presented either in the original scene or on a white background. A series of behavioral studies with young adults demonstrated a context shift decrement (CSD)-decreased recognition performance when context is changed between encoding and retrieval. The CSD was not attenuated by encoding or retrieval manipulations, suggesting that binding of object and context may be automatic. A final experiment explored the neural correlates of the CSD, using functional Magnetic Resonance Imaging. Parahippocampal cortex (PHC) activation (right greater than left) during incidental encoding was associated with subsequent memory of objects in the context shift condition. Greater activity in right PHC was also observed during successful recognition of objects previously presented in a scene. Finally, a subset of regions activated during scene encoding, such as bilateral PHC, was reactivated when the object was presented on a white background at retrieval. Although participants were not required to intentionally retrieve contextual information, the results suggest that PHC may reinstate visual context to mediate successful episodic memory retrieval. The CSD is attributed to automatic and obligatory binding of object and context. The results suggest that PHC is important not only for processing of scene information, but also plays a role in successful episodic memory encoding and retrieval. These findings are consistent with the view that spatial information is stored in the hippocampal complex, one of the central tenets of Multiple Trace Theory. (c) 2007 Wiley-Liss, Inc.

  14. Chronic methylphenidate-effects over circadian cycle of young and adult rats submitted to open-field and object recognition tests.

    PubMed

    Gomes, Karin M; Souza, Renan P; Valvassori, Samira S; Réus, Gislaine Z; Inácio, Cecília G; Martins, Márcio R; Comim, Clarissa M; Quevedo, João

    2009-11-01

    In this study age-, circadian rhythm- and methylphenidate administration- effect on open field habituation and object recognition were analyzed. Young and adult male Wistar rats were treated with saline or methylphenidate 2.0 mg/kg for 28 days. Experiments were performed during the light and the dark cycle. Locomotor activity was significantly altered by circadian cycle and methylphenidate treatment during the training session and by drug treatment during the testing session. Exploratory activity was significantly modulated by age during the training session and by age and drug treatment during the testing session. Object recognition memory was altered by cycle at the training session; by age 1.5 h later and by cycle and age 24 h after the training session. These results show that methylphenidate treatment was the major modulator factor on open-field test while cycle and age had an important effect on object recognition experiment.

  15. Cortical Thickness in Fusiform Face Area Predicts Face and Object Recognition Performance

    PubMed Central

    McGugin, Rankin W.; Van Gulick, Ana E.; Gauthier, Isabel

    2016-01-01

    The fusiform face area (FFA) is defined by its selectivity for faces. Several studies have shown that the response of FFA to non-face objects can predict behavioral performance for these objects. However, one possible account is that experts pay more attention to objects in their domain of expertise, driving signals up. Here we show an effect of expertise with non-face objects in FFA that cannot be explained by differential attention to objects of expertise. We explore the relationship between cortical thickness of FFA and face and object recognition using the Cambridge Face Memory Test and Vanderbilt Expertise Test, respectively. We measured cortical thickness in functionally-defined regions in a group of men who evidenced functional expertise effects for cars in FFA. Performance with faces and objects together accounted for approximately 40% of the variance in cortical thickness of several FFA patches. While subjects with a thicker FFA cortex performed better with vehicles, those with a thinner FFA cortex performed better with faces and living objects. The results point to a domain-general role of FFA in object perception and reveal an interesting double dissociation that does not contrast faces and objects, but rather living and non-living objects. PMID:26439272

  16. A model of attention-guided visual perception and recognition.

    PubMed

    Rybak, I A; Gusakova, V I; Golovan, A V; Podladchikova, L N; Shevtsova, N A

    1998-08-01

    A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.

  17. A role for calcium-calmodulin-dependent protein kinase II in the consolidation of visual object recognition memory.

    PubMed

    Tinsley, C J; Narduzzo, K E; Ho, J W; Barker, G R; Brown, M W; Warburton, E C

    2009-09-01

    The aim was to investigate the role of calcium-calmodulin-dependent protein kinase (CAMK)II in object recognition memory. The performance of rats in a preferential object recognition test was examined after local infusion of the CAMKII inhibitors KN-62 or autocamtide-2-related inhibitory peptide (AIP) into the perirhinal cortex. KN-62 or AIP infused after acquisition impaired memory tested at 24 h, indicating an involvement of CAMKII in the consolidation of recognition memory. Memory was impaired when KN-62 was infused at 20 min after acquisition or when AIP was infused at 20, 40, 60 or 100 min after acquisition. The time-course of CAMKII activation in rats was further examined by immunohistochemical staining for phospho-CAMKII(Thre286)alpha at 10, 40, 70 and 100 min following the viewing of novel and familiar images. At 70 min, processing novel images resulted in more phospho-CAMKII(Thre286)alpha-stained neurons in the perirhinal cortex than did the processing of familiar images, consistent with the viewing of novel images increasing the activity of CAMKII at this time. This difference was eliminated by prior infusion of AIP. These findings establish that CAMKII is active within the perirhinal region between approximately 20 and 100 min following learning and then returns to baseline. Thus, increased CAMKII activity is essential for the consolidation of long-term object recognition memory but continuation of that increased activity throughout the 24 h memory delay is not necessary for maintenance of the memory.

  18. Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

    ERIC Educational Resources Information Center

    Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

    2010-01-01

    Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

  19. A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

    PubMed

    Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

    2014-01-01

    Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

  20. A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

    PubMed Central

    Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

    2014-01-01

    Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

  1. One-Reason Decision Making Unveiled: A Measurement Model of the Recognition Heuristic

    ERIC Educational Resources Information Center

    Hilbig, Benjamin E.; Erdfelder, Edgar; Pohl, Rudiger F.

    2010-01-01

    The fast-and-frugal recognition heuristic (RH) theory provides a precise process description of comparative judgments. It claims that, in suitable domains, judgments between pairs of objects are based on recognition alone, whereas further knowledge is ignored. However, due to the confound between recognition and further knowledge, previous…

  2. Modafinil improves methamphetamine-induced object recognition deficits and restores prefrontal cortex ERK signaling in mice.

    PubMed

    González, Betina; Raineri, Mariana; Cadet, Jean Lud; García-Rill, Edgar; Urbano, Francisco J; Bisagno, Veronica

    2014-12-01

    Chronic use of methamphetamine (METH) leads to long-lasting cognitive dysfunction in humans and in animal models. Modafinil is a wake-promoting compound approved for the treatment of sleeping disorders. It is also prescribed off label to treat METH dependence. In the present study, we investigated whether modafinil could improve cognitive deficits induced by sub-chronic METH treatment in mice by measuring visual retention in a Novel Object Recognition (NOR) task. After sub-chronic METH treatment (1 mg/kg, once a day for 7 days), mice performed the NOR task, which consisted of habituation to the object recognition arena (5 min a day, 3 consecutive days), training session (2 equal objects, 10 min, day 4), and a retention session (1 novel object, 5 min, day 5). One hour before the training session, mice were given a single dose of modafinil (30 or 90 mg/kg). METH-treated mice showed impairments in visual memory retention, evidenced by equal preference of familiar and novel objects during the retention session. The lower dose of modafinil (30 mg/kg) had no effect on visual retention scores in METH-treated mice, while the higher dose (90 mg/kg) rescued visual memory retention to control values. We also measured extracellular signal-regulated kinase (ERK) phosphorylation in medial prefrontal cortex (mPFC), hippocampus, and nucleus accumbens (NAc) of METH- and vehicle-treated mice that received modafinil 1 h before exposure to novel objects in the training session, compared to mice placed in the arena without objects. Elevated ERK phosphorylation was found in the mPFC of vehicle-treated mice, but not in METH-treated mice, exposed to objects. The lower dose of modafinil had no effect on ERK phosphorylation in METH-treated mice, while 90 mg/kg modafinil treatment restored the ERK phosphorylation induced by novelty in METH-treated mice to values comparable to controls. We found neither a novelty nor treatment effect on ERK phosphorylation in hippocampus or NAc of vehicle

  3. Good initialization model with constrained body structure for scene text recognition

    NASA Astrophysics Data System (ADS)

    Zhu, Anna; Wang, Guoyou; Dong, Yangbo

    2016-09-01

    Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

  4. Implementation of a Peltier-based cooling device for localized deep cortical deactivation during in vivo object recognition testing

    NASA Astrophysics Data System (ADS)

    Marra, Kyle; Graham, Brett; Carouso, Samantha; Cox, David

    2012-02-01

    While the application of local cortical cooling has recently become a focus of neurological research, extended localized deactivation deep within brain structures is still unexplored. Using a wirelessly controlled thermoelectric (Peltier) device and water-based heat sink, we have achieved inactivating temperatures (<20 C) at greater depths (>8 mm) than previously reported. After implanting the device into Long Evans rats' basolateral amygdala (BLA), an inhibitory brain center that controls anxiety and fear, we ran an open field test during which anxiety-driven behavioral tendencies were observed to decrease during cooling, thus confirming the device's effect on behavior. Our device will next be implanted in the rats' temporal association cortex (TeA) and recordings from our signal-tracing multichannel microelectrodes will measure and compare activated and deactivated neuronal activity so as to isolate and study the TeA signals responsible for object recognition. Having already achieved a top performing computational face-recognition system, the lab will utilize this TeA activity data to generalize its computational efforts of face recognition to achieve general object recognition.

  5. OPTICAL INFORMATION PROCESSING: Synthesis of an object recognition system based on the profile of the envelope of a laser pulse in pulsed lidars

    NASA Astrophysics Data System (ADS)

    Buryi, E. V.

    1998-05-01

    The main problems in the synthesis of an object recognition system, based on the principles of operation of neuron networks, are considered. Advantages are demonstrated of a hierarchical structure of the recognition algorithm. The use of reading of the amplitude spectrum of signals as information tags is justified and a method is developed for determination of the dimensionality of the tag space. Methods are suggested for ensuring the stability of object recognition in the optical range. It is concluded that it should be possible to recognise perspectives of complex objects.

  6. Infrared detection, recognition and identification of handheld objects

    NASA Astrophysics Data System (ADS)

    Adomeit, Uwe

    2012-10-01

    A main criterion for comparison and selection of thermal imagers for military applications is their nominal range performance. This nominal range performance is calculated for a defined task and standardized target and environmental conditions. The only standardization available to date is STANAG 4347. The target defined there is based on a main battle tank in front view. Because of modified military requirements, this target is no longer up-to-date. Today, different topics of interest are of interest, especially differentiation between friend and foe and identification of humans. There is no direct way to differentiate between friend and foe in asymmetric scenarios, but one clue can be that someone is carrying a weapon. This clue can be transformed in the observer tasks detection: a person is carrying or is not carrying an object, recognition: the object is a long / medium / short range weapon or civil equipment and identification: the object can be named (e. g. AK-47, M-4, G36, RPG7, Axe, Shovel etc.). These tasks can be assessed experimentally and from the results of such an assessment, a standard target for handheld objects may be derived. For a first assessment, a human carrying 13 different handheld objects in front of his chest was recorded at four different ranges with an IR-dual-band camera. From the recorded data, a perception experiment was prepared. It was conducted with 17 observers in a 13-alternative forced choice, unlimited observation time arrangement. The results of the test together with Minimum Temperature Difference Perceived measurements of the camera and temperature difference and critical dimension derived from the recorded imagery allowed defining a first standard target according to the above tasks. This standard target consist of 2.5 / 3.5 / 5 DRI line pairs on target, 0.24 m critical size and 1 K temperature difference. The values are preliminary and have to be refined in the future. Necessary are different aspect angles, different

  7. Emotional valence of stimuli modulates false recognition: Using a modified version of the simplified conjoint recognition paradigm.

    PubMed

    Gong, Xianmin; Xiao, Hongrui; Wang, Dahua

    2016-11-01

    False recognition results from the interplay of multiple cognitive processes, including verbatim memory, gist memory, phantom recollection, and response bias. In the current study, we modified the simplified Conjoint Recognition (CR) paradigm to investigate the way in which the valence of emotional stimuli affects the cognitive process and behavioral outcome of false recognition. In Study 1, we examined the applicability of the modification to the simplified CR paradigm and model. Twenty-six undergraduate students (13 females, aged 21.00±2.30years) learned and recognized both the large and small categories of photo objects. The applicability of the paradigm and model was confirmed by a fair goodness-of-fit of the model to the observational data and by their competence in detecting the memory differences between the large- and small-category conditions. In Study 2, we recruited another sample of 29 undergraduate students (14 females, aged 22.60±2.74years) to learn and recognize the categories of photo objects that were emotionally provocative. The results showed that negative valence increased false recognition, particularly the rate of false "remember" responses, by facilitating phantom recollection; positive valence did not influence false recognition significantly though enhanced gist processing. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. A method of 3D object recognition and localization in a cloud of points

    NASA Astrophysics Data System (ADS)

    Bielicki, Jerzy; Sitnik, Robert

    2013-12-01

    The proposed method given in this article is prepared for analysis of data in the form of cloud of points directly from 3D measurements. It is designed for use in the end-user applications that can directly be integrated with 3D scanning software. The method utilizes locally calculated feature vectors (FVs) in point cloud data. Recognition is based on comparison of the analyzed scene with reference object library. A global descriptor in the form of a set of spatially distributed FVs is created for each reference model. During the detection process, correlation of subsets of reference FVs with FVs calculated in the scene is computed. Features utilized in the algorithm are based on parameters, which qualitatively estimate mean and Gaussian curvatures. Replacement of differentiation with averaging in the curvatures estimation makes the algorithm more resistant to discontinuities and poor quality of the input data. Utilization of the FV subsets allows to detect partially occluded and cluttered objects in the scene, while additional spatial information maintains false positive rate at a reasonably low level.

  9. Better object recognition and naming outcome with MRI-guided stereotactic laser amygdalohippocampotomy for temporal lobe epilepsy.

    PubMed

    Drane, Daniel L; Loring, David W; Voets, Natalie L; Price, Michele; Ojemann, Jeffrey G; Willie, Jon T; Saindane, Amit M; Phatak, Vaishali; Ivanisevic, Mirjana; Millis, Scott; Helmers, Sandra L; Miller, John W; Meador, Kimford J; Gross, Robert E

    2015-01-01

    Patients with temporal lobe epilepsy (TLE) experience significant deficits in category-related object recognition and naming following standard surgical approaches. These deficits may result from a decoupling of core processing modules (e.g., language, visual processing, and semantic memory), due to "collateral damage" to temporal regions outside the hippocampus following open surgical approaches. We predicted that stereotactic laser amygdalohippocampotomy (SLAH) would minimize such deficits because it preserves white matter pathways and neocortical regions that are critical for these cognitive processes. Tests of naming and recognition of common nouns (Boston Naming Test) and famous persons were compared with nonparametric analyses using exact tests between a group of 19 patients with medically intractable mesial TLE undergoing SLAH (10 dominant, 9 nondominant), and a comparable series of TLE patients undergoing standard surgical approaches (n=39) using a prospective, nonrandomized, nonblinded, parallel-group design. Performance declines were significantly greater for the patients with dominant TLE who were undergoing open resection versus SLAH for naming famous faces and common nouns (F=24.3, p<0.0001, η2=0.57, and F=11.2, p<0.001, η2=0.39, respectively), and for the patients with nondominant TLE undergoing open resection versus SLAH for recognizing famous faces (F=3.9, p<0.02, η2=0.19). When examined on an individual subject basis, no SLAH patients experienced any performance declines on these measures. In contrast, 32 of the 39 patients undergoing standard surgical approaches declined on one or more measures for both object types (p<0.001, Fisher's exact test). Twenty-one of 22 left (dominant) TLE patients declined on one or both naming tasks after open resection, while 11 of 17 right (nondominant) TLE patients declined on face recognition. Preliminary results suggest (1) naming and recognition functions can be spared in TLE patients undergoing SLAH, and (2

  10. Simulated Prosthetic Vision: The Benefits of Computer-Based Object Recognition and Localization.

    PubMed

    Macé, Marc J-M; Guivarch, Valérian; Denis, Grégoire; Jouffrais, Christophe

    2015-07-01

    Clinical trials with blind patients implanted with a visual neuroprosthesis showed that even the simplest tasks were difficult to perform with the limited vision restored with current implants. Simulated prosthetic vision (SPV) is a powerful tool to investigate the putative functions of the upcoming generations of visual neuroprostheses. Recent studies based on SPV showed that several generations of implants will be required before usable vision is restored. However, none of these studies relied on advanced image processing. High-level image processing could significantly reduce the amount of information required to perform visual tasks and help restore visuomotor behaviors, even with current low-resolution implants. In this study, we simulated a prosthetic vision device based on object localization in the scene. We evaluated the usability of this device for object recognition, localization, and reaching. We showed that a very low number of electrodes (e.g., nine) are sufficient to restore visually guided reaching movements with fair timing (10 s) and high accuracy. In addition, performance, both in terms of accuracy and speed, was comparable with 9 and 100 electrodes. Extraction of high level information (object recognition and localization) from video images could drastically enhance the usability of current visual neuroprosthesis. We suggest that this method-that is, localization of targets of interest in the scene-may restore various visuomotor behaviors. This method could prove functional on current low-resolution implants. The main limitation resides in the reliability of the vision algorithms, which are improving rapidly. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  11. Recognition-induced forgetting of faces in visual long-term memory.

    PubMed

    Rugo, Kelsi F; Tamler, Kendall N; Woodman, Geoffrey F; Maxcey, Ashleigh M

    2017-10-01

    Despite more than a century of evidence that long-term memory for pictures and words are different, much of what we know about memory comes from studies using words. Recent research examining visual long-term memory has demonstrated that recognizing an object induces the forgetting of objects from the same category. This recognition-induced forgetting has been shown with a variety of everyday objects. However, unlike everyday objects, faces are objects of expertise. As a result, faces may be immune to recognition-induced forgetting. However, despite excellent memory for such stimuli, we found that faces were susceptible to recognition-induced forgetting. Our findings have implications for how models of human memory account for recognition-induced forgetting as well as represent objects of expertise and consequences for eyewitness testimony and the justice system.

  12. Three-dimensional deformable-model-based localization and recognition of road vehicles.

    PubMed

    Zhang, Zhaoxiang; Tan, Tieniu; Huang, Kaiqi; Wang, Yunhong

    2012-01-01

    We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D deformable vehicle model with 12 shape parameters is set up as prior information, and its pose is determined by three parameters, which are its position on the ground plane and its orientation about the vertical axis under ground-plane constraints. An efficient local gradient-based method is proposed to evaluate the fitness between the projection of the vehicle model and image data, which is combined into a novel evolutionary computing framework to estimate the 12 shape parameters and three pose parameters by iterative evolution. The recovery of pose parameters achieves vehicle localization, whereas the shape parameters are used for vehicle recognition. Numerous experiments are conducted in this paper to demonstrate the performance of our approach. It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data. The evolutionary computing framework is effective for vehicles of different types and poses is robust to all kinds of occlusion.

  13. Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

    NASA Astrophysics Data System (ADS)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

    2009-04-01

    θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

  14. Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

    PubMed Central

    Azzopardi, George; Petkov, Nicolai

    2014-01-01

    The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068

  15. Vehicle logo recognition using multi-level fusion model

    NASA Astrophysics Data System (ADS)

    Ming, Wei; Xiao, Jianli

    2018-04-01

    Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.

  16. Formal Models of Word Recognition. Final Report.

    ERIC Educational Resources Information Center

    Travers, Jeffrey R.

    Existing mathematical models of word recognition are reviewed and a new theory is proposed in this research. The new theory integrates earlier proposals within a single framework, sacrificing none of the predictive power of the earlier proposals, but offering a gain in theoretical economy. The theory holds that word recognition is accomplished by…

  17. Multi-modal gesture recognition using integrated model of motion, audio and video

    NASA Astrophysics Data System (ADS)

    Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

    2015-07-01

    Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

  18. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms

    PubMed Central

    Schädler, Marc R.; Warzybok, Anna; Kollmeier, Birger

    2018-01-01

    The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted. PMID:29692200

  19. Depth rotation and mirror-image reflection reduce affective preference as well as recognition memory for pictures of novel objects.

    PubMed

    Lawson, Rebecca

    2004-10-01

    In two experiments, the identification of novel 3-D objects was worse for depth-rotated and mirror-reflected views, compared with the study view in an implicit affective preference memory task, as well as in an explicit recognition memory task. In Experiment 1, recognition was worse and preference was lower when depth-rotated views of an object were paired with an unstudied object relative to trials when the study view of that object was shown. There was a similar trend for mirror-reflected views. In Experiment 2, the study view of an object was both recognized and preferred above chance when it was paired with either depth-rotated or mirror-reflected views of that object. These results suggest that view-sensitive representations of objects mediate performance in implicit, as well as explicit, memory tasks. The findings do not support the claim that separate episodic and structural description representations underlie performance in implicit and explicit memory tasks, respectively.

  20. Short-term blueberry-enriched diet prevents and reverses object recognition memory loss in aging rats.

    PubMed

    Malin, David H; Lee, David R; Goyarzu, Pilar; Chang, Yu-Hsuan; Ennis, Lalanya J; Beckett, Elizabeth; Shukitt-Hale, Barbara; Joseph, James A

    2011-03-01

    Previously, 4 mo of a blueberry-enriched (BB) antioxidant diet prevented impaired object recognition memory in aging rats. Experiment 1 determined whether 1- and 2-mo BB diets would have a similar effect and whether the benefits would disappear promptly after terminating the diets. Experiment 2 determined whether a 1-mo BB diet could subsequently reverse existing object memory impairment in aging rats. In experiment 1, Fischer-344 rats were maintained on an appropriate control diet or on 1 or 2 mo of the BB diet before testing object memory at 19 mo postnatally. In experiment 2, rats were tested for object recognition memory at 19 mo and again at 20 mo after 1 mo of maintenance on a 2% BB or control diet. In experiment 1, the control group performed no better than chance, whereas the 1- and 2-mo BB diet groups performed similarly and significantly better than controls. The 2-mo BB-diet group, but not the 1-mo group, maintained its performance over a subsequent month on a standard laboratory diet. In experiment 2, the 19-mo-old rats performed near chance. At 20 mo of age, the rats subsequently maintained on the BB diet significantly increased their object memory scores, whereas the control diet group exhibited a non-significant decline. The change in object memory scores differed significantly between the two diet groups. These results suggest that a considerable degree of age-related object memory decline can be prevented and reversed by brief maintenance on BB diets. Copyright © 2011 Elsevier Inc. All rights reserved.

  1. The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

    ERIC Educational Resources Information Center

    Wood, Justin N.; Wood, Samantha M. W.

    2018-01-01

    How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

  2. Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

    ERIC Educational Resources Information Center

    Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

    2004-01-01

    Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

  3. Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

    DOE PAGES

    Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

    2014-10-23

    Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

  4. Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

    Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

  5. A model of traffic signs recognition with convolutional neural network

    NASA Astrophysics Data System (ADS)

    Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

    2016-10-01

    In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

  6. PHYSICAL MODEL FOR RECOGNITION TUNNELING

    PubMed Central

    Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

    2015-01-01

    Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

  7. Speaker-independent phoneme recognition with a binaural auditory image model

    NASA Astrophysics Data System (ADS)

    Francis, Keith Ivan

    1997-09-01

    This dissertation presents phoneme recognition techniques based on a binaural fusion of outputs of the auditory image model and subsequent azimuth-selective phoneme recognition in a noisy environment. Background information concerning speech variations, phoneme recognition, current binaural fusion techniques and auditory modeling issues is explained. The research is constrained to sources in the frontal azimuthal plane of a simulated listener. A new method based on coincidence detection of neural activity patterns from the auditory image model of Patterson is used for azimuth-selective phoneme recognition. The method is tested in various levels of noise and the results are reported in contrast to binaural fusion methods based on various forms of correlation to demonstrate the potential of coincidence- based binaural phoneme recognition. This method overcomes smearing of fine speech detail typical of correlation based methods. Nevertheless, coincidence is able to measure similarity of left and right inputs and fuse them into useful feature vectors for phoneme recognition in noise.

  8. Divergent short- and long-term effects of acute stress in object recognition memory are mediated by endogenous opioid system activation.

    PubMed

    Nava-Mesa, Mauricio O; Lamprea, Marisol R; Múnera, Alejandro

    2013-11-01

    Acute stress induces short-term object recognition memory impairment and elicits endogenous opioid system activation. The aim of this study was thus to evaluate whether opiate system activation mediates the acute stress-induced object recognition memory changes. Adult male Wistar rats were trained in an object recognition task designed to test both short- and long-term memory. Subjects were randomly assigned to receive an intraperitoneal injection of saline, 1 mg/kg naltrexone or 3 mg/kg naltrexone, four and a half hours before the sample trial. Five minutes after the injection, half the subjects were submitted to movement restraint during four hours while the other half remained in their home cages. Non-stressed subjects receiving saline (control) performed adequately during the short-term memory test, while stressed subjects receiving saline displayed impaired performance. Naltrexone prevented such deleterious effect, in spite of the fact that it had no intrinsic effect on short-term object recognition memory. Stressed subjects receiving saline and non-stressed subjects receiving naltrexone performed adequately during the long-term memory test; however, control subjects as well as stressed subjects receiving a high dose of naltrexone performed poorly. Control subjects' dissociated performance during both memory tests suggests that the short-term memory test induced a retroactive interference effect mediated through light opioid system activation; such effect was prevented either by low dose naltrexone administration or by strongly activating the opioid system through acute stress. Both short-term memory retrieval impairment and long-term memory improvement observed in stressed subjects may have been mediated through strong opioid system activation, since they were prevented by high dose naltrexone administration. Therefore, the activation of the opioid system plays a dual modulating role in object recognition memory. Copyright © 2013 Elsevier Inc. All rights

  9. Heterozygous Che-1 KO mice show deficiencies in object recognition memory persistence.

    PubMed

    Zalcman, Gisela; Corbi, Nicoletta; Di Certo, Maria Grazia; Mattei, Elisabetta; Federman, Noel; Romano, Arturo

    2016-10-06

    Transcriptional regulation is a key process in the formation of long-term memories. Che-1 is a protein involved in the regulation of gene transcription that has recently been proved to bind the transcription factor NF-κB, which is known to be involved in many memory-related molecular events. This evidence prompted us to investigate the putative role of Che-1 in memory processes. For this study we newly generated a line of Che-1(+/-) heterozygous mice. Che-1 homozygous KO mouse is lethal during development, but Che-1(+/-) heterozygous mouse is normal in its general anatomical and physiological characteristics. We analyzed the behavioral characteristic and memory performance of Che-1(+/-) mice in two NF-κB dependent types of memory. We found that Che-1(+/-) mice show similar locomotor activity and thigmotactic behavior than wild type (WT) mice in an open field. In a similar way, no differences were found in anxiety-like behavior between Che-1(+/-) and WT mice in an elevated plus maze as well as in fear response in a contextual fear conditioning (CFC) and object exploration in a novel object recognition (NOR) task. No differences were found between WT and Che-1(+/-) mice performance in CFC training and when tested at 24h or 7days after training. Similar performance was found between groups in NOR task, both in training and 24h testing performance. However, we found that object recognition memory persistence at 7days was impaired in Che-1(+/-) heterozygous mice. This is the first evidence showing that Che-1 is involved in memory processes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  10. Shape analysis modeling for character recognition

    NASA Astrophysics Data System (ADS)

    Khan, Nadeem A. M.; Hegt, Hans A.

    1998-10-01

    Optimal shape modeling of character-classes is crucial for achieving high performance on recognition of mixed-font, hand-written or (and) poor quality text. A novel scheme is presented in this regard focusing on constructing such structural models that can be hierarchically examined. These models utilize a certain `well-thought' set of shape primitives. They are simplified enough to ignore the inter- class variations in font-type or writing style yet retaining enough details for discrimination between the samples of the similar classes. Thus the number of models per class required can be kept minimal without sacrificing the recognition accuracy. In this connection a flexible multi- stage matching scheme exploiting the proposed modeling is also described. This leads to a system which is robust against various distortions and degradation including those related to cases of touching and broken characters. Finally, we present some examples and test results as a proof-of- concept demonstrating the validity and the robustness of the approach.

  11. [Research progress of multi-model medical image fusion and recognition].

    PubMed

    Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

    2013-10-01

    Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

  12. Automation of the novel object recognition task for use in adolescent rats

    PubMed Central

    Silvers, Janelle M.; Harrod, Steven B.; Mactutus, Charles F.; Booze, Rosemarie M.

    2010-01-01

    The novel object recognition task is gaining popularity for its ability to test a complex behavior which relies on the integrity of memory and attention systems without placing undue stress upon the animal. While the task places few requirements upon the animal, it traditionally requires the experimenter to observe the test phase directly and record behavior. This approach can severely limit the number of subjects which can be tested in a reasonable period of time, as training and testing occur on the same day and span several hours. The current study was designed to test the feasibility of automation of this task for adolescent rats using standard activity chambers, with the goals of increased objectivity, flexibility, and throughput of subjects. PMID:17719091

  13. Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition

    PubMed Central

    Janko, Vito

    2017-01-01

    The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301

  14. A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

    NASA Astrophysics Data System (ADS)

    Möller, Manuel; Tuot, Christopher; Sintek, Michael

    In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

  15. Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

    PubMed Central

    Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

    2016-01-01

    Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees’ flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots. PMID:26886006

  16. Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

    PubMed

    Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

    2016-01-01

    Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

  17. Real-time optical multiple object recognition and tracking system and method

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin (Inventor); Liu, Hua-Kuang (Inventor)

    1990-01-01

    System for optically recognizing and tracking a plurality of objects within a field of vision. Laser (46) produces a coherent beam (48). Beam splitter (24) splits the beam into object (26) and reference (28) beams. Beam expanders (50) and collimators (52) transform the beams (26, 28) into coherent collimated light beams (26', 28'). A two-dimensional SLM (54), disposed in the object beam (26'), modulates the object beam with optical information as a function of signals from a first camera (16) which develops X and Y signals reflecting the contents of its field of vision. A hololens (38), positioned in the object beam (26') subsequent to the modulator (54), focuses the object beam at a plurality of focal points (42). A planar transparency-forming film (32), disposed with the focal points on an exposable surface, forms a multiple position interference filter (62) upon exposure of the surface and development processing of the film (32). A reflector (53) directing the reference beam (28') onto the film (32), exposes the surface, with images focused by the hololens (38), to form interference patterns on the surface. There is apparatus (16', 64) for sensing and indicating light passage through respective ones of the positions of the filter (62), whereby recognition of objects corresponding to respective ones of the positions of the filter (62) is affected. For tracking, apparatus (64) focuses light passing through the filter (62) onto a matrix of CCD's in a second camera (16') to form a two-dimensional display of the recognized objects.

  18. Improving human object recognition performance using video enhancement techniques

    NASA Astrophysics Data System (ADS)

    Whitman, Lucy S.; Lewis, Colin; Oakley, John P.

    2004-12-01

    Atmospheric scattering causes significant degradation in the quality of video images, particularly when imaging over long distances. The principle problem is the reduction in contrast due to scattered light. It is known that when the scattering particles are not too large compared with the imaging wavelength (i.e. Mie scattering) then high spatial resolution information may be contained within a low-contrast image. Unfortunately this information is not easily perceived by a human observer, particularly when using a standard video monitor. A secondary problem is the difficulty of achieving a sharp focus since automatic focus techniques tend to fail in such conditions. Recently several commercial colour video processing systems have become available. These systems use various techniques to improve image quality in low contrast conditions whilst retaining colour content. These systems produce improvements in subjective image quality in some situations, particularly in conditions of haze and light fog. There is also some evidence that video enhancement leads to improved ATR performance when used as a pre-processing stage. Psychological literature indicates that low contrast levels generally lead to a reduction in the performance of human observers in carrying out simple visual tasks. The aim of this paper is to present the results of an empirical study on object recognition in adverse viewing conditions. The chosen visual task was vehicle number plate recognition at long ranges (500 m and beyond). Two different commercial video enhancement systems are evaluated using the same protocol. The results show an increase in effective range with some differences between the different enhancement systems.

  19. Hybrid Speaker Recognition Using Universal Acoustic Model

    NASA Astrophysics Data System (ADS)

    Nishimura, Jun; Kuroda, Tadahiro

    We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

  20. Bilevel Model-Based Discriminative Dictionary Learning for Recognition.

    PubMed

    Zhou, Pan; Zhang, Chao; Lin, Zhouchen

    2017-03-01

    Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the l 0 or l 1 norm to encode each datum independently, limiting the performance of the learnt dictionaries. We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks. The upper level directly minimizes the classification error, while the lower level uses the sparsity term and the Laplacian term to characterize the intrinsic data structure. The lower level is subordinate to the upper level. Therefore, our model achieves an overall optimality for recognition in that the learnt dictionary is directly tailored for recognition. Moreover, the sparse codes learning models in the training and the testing phases can be the same. We further propose a novel method to solve our bilevel optimization problem. It first replaces the lower level with its Karush-Kuhn-Tucker conditions and then applies the alternating direction method of multipliers to solve the equivalent problem. Extensive experiments demonstrate the effectiveness and robustness of our method.

  1. The Role of Competitive Inhibition and Top-Down Feedback in Binding during Object Recognition

    PubMed Central

    Wyatte, Dean; Herd, Seth; Mingus, Brian; O’Reilly, Randall

    2012-01-01

    How does the brain bind together visual features that are processed concurrently by different neurons into a unified percept suitable for processes such as object recognition? Here, we describe how simple, commonly accepted principles of neural processing can interact over time to solve the brain’s binding problem. We focus on mechanisms of neural inhibition and top-down feedback. Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions. Top-down feedback contributes to binding in a similar manner, but by reinforcing relevant features. Together, inhibition and top-down feedback contribute to a competitive environment that ensures only the most appropriate features are bound together. We demonstrate this overall proposal using a biologically realistic neural model of vision that processes features across a hierarchy of interconnected brain areas. Finally, we argue that temporal synchrony plays only a limited role in binding – it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features. Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes. PMID:22719733

  2. Automatic anatomy recognition in whole-body PET/CT images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Huiqian; Udupa, Jayaram K., E-mail: jay@mail.med.upenn.edu; Odhner, Dewey

    Purpose: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity ofmore » anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the

  3. Implications of Animal Object Memory Research for Human Amnesia

    ERIC Educational Resources Information Center

    Winters, Boyer D.; Saksida, Lisa M.; Bussey, Timothy J.

    2010-01-01

    Damage to structures in the human medial temporal lobe causes severe memory impairment. Animal object recognition tests gained prominence from attempts to model "global" human medial temporal lobe amnesia, such as that observed in patient HM. These tasks, such as delayed nonmatching-to-sample and spontaneous object recognition, for assessing…

  4. The "Decorative" Female Model: Sexual Stimuli and the Recognition of Advertisements

    ERIC Educational Resources Information Center

    LaChance, Charles C.; And Others

    1977-01-01

    Examines the impact of the decorative or functionless female models in print advertising and indicates that models facilitate recognition of model/related information but do little to increase the recognition of brand names.

  5. Effect of (+)-Methamphetamine on Path Integration Learning, Novel Object Recognition, and Neurotoxicity in Rats

    PubMed Central

    Herring, Nicole R.; Schaefer, Tori L.; Gudelsky, Gary A.; Vorhees, Charles V.; Williams, Michael T.

    2008-01-01

    Rationale Methamphetamine (MA) has been implicated in cognitive deficits in humans after chronic use. Animal models of neurotoxic MA exposure reveal persistent damage to monoaminergic systems, but few associated cognitive effects. Objectives Since, questions have been raised about the typical neurotoxic dosing regimen used in animals and whether it adequately models human cumulative drug exposure, these experiments examined two different dosing regimens. Methods Rats were treated with one of two regimens, one the typical neurotoxic regimen (4 × 10 mg/kg every 2 h) and one based on pharmacokinetic modeling (Cho et al. 2001) designed to better represent accumulating plasma concentrations of MA as seen in human users (24 ×1.67 mg/kg once every 15 min); matched for total daily dose. In two separate experiments, dosing regimens were compared for their effects on markers of neurotoxicity or on behavior. Results On markers of neurotoxicity, MA showed decreased DA and 5-HT, and increased glial fibrillary acidic protein and increased corticosterone levels regardless of dosing regimen 3 days post-treatment. Behaviorally, MA-treated groups, regardless of dosing regimen, showed hypoactivity, increased initial hyperactivity to a subsequent MA challenge, impaired novel object recognition, impaired learning in a multiple-T water maze test of path integration, and no differences on spatial navigation or reference memory in the Morris water maze. After behavioral testing, reductions of DA and 5-HT remained. Conclusions MA treatment induces an effect on path integration learning not previously reported. Dosing regimen had no differential effects on behavior or neurotoxicity. PMID:18509623

  6. Bacopa monnieri (Brahmi) improved novel object recognition task and increased cerebral vesicular glutamate transporter type 3 in sub-chronic phencyclidine rat model of schizophrenia.

    PubMed

    Piyabhan, Pritsana; Wannasiri, Supaporn; Naowaboot, Jarinyaporn

    2016-12-01

    Reduced vesicular glutamate transporter 1 (VGLUT1) and 2 (VGLUT2) indicate glutamatergic hypofunction leading to cognitive impairment in schizophrenia. However, VGLUT3 involvement in cognitive dysfunction has not been reported in schizophrenia. Brahmi (Bacopa monnieri) might be a new treatment and prevention for cognitive deficits in schizophrenia by acting on cerebral VGLUT3 density. We aimed to study cognitive enhancement- and neuroprotective-effects of Brahmi on novel object recognition and cerebral VGLUT3 immunodensity in sub-chronic (2 mg/kg, Bid, ip) phencyclidine (PCP) rat model of schizophrenia. Rats were assigned to three groups for cognitive enhancement effect study: Group 1, Control; Group 2, PCP administration; Group 3, PCP+Brahmi. A neuroprotective-effect study was also carried out. Rats were again assigned to three groups: Group 1, Control; Group 2, PCP administration; Group 3, Brahmi+PCP. Discrimination ratio (DR) representing cognitive ability was obtained from a novel object recognition task. VGLUT3 immunodensity was measured in the prefrontal cortex, striatum and cornu ammonis fields 1-3 (CA1-3) using immunohistochemistry. We found reduced DR in the PCP group, which occurred alongside VGLUT3 reduction in all brain areas. PCP+Brahmi showed higher DR score with increased VGLUT3 immunodensity in the prefrontal cortex and striatum. Brahmi+PCP group showed a higher DR score with increased VGLUT3 immunodensity in the prefrontal cortex, striatum and CA1-3. We concluded that reduced cerebral VGLUT3 was involved in cognitive deficit in PCP-administrated rats. Receiving Brahmi after PCP restored cognitive deficit by increasing VGLUT3 in the prefrontal cortex and striatum. Receiving Brahmi before PCP prevented cognitive impairment by elevating VGLUT3 in prefrontal cortex, striatum and CA1-3. Therefore, Brahmi could be a new frontier of restoration and prevention of cognitive deficit in schizophrenia. © 2016 John Wiley & Sons Australia, Ltd.

  7. Differing time dependencies of object recognition memory impairments produced by nicotinic and muscarinic cholinergic antagonism in perirhinal cortex

    PubMed Central

    Tinsley, Chris J.; Fontaine-Palmer, Nadine S.; Vincent, Maria; Endean, Emma P.E.; Aggleton, John P.; Brown, Malcolm W.; Warburton, E. Clea

    2011-01-01

    The roles of muscarinic and nicotinic cholinergic receptors in perirhinal cortex in object recognition memory were compared. Rats' discrimination of a novel object preference test (NOP) test was measured after either systemic or local infusion into the perirhinal cortex of the nicotinic receptor antagonist methyllycaconitine (MLA), which targets alpha-7 (α7) amongst other nicotinic receptors or the muscarinic receptor antagonists scopolamine, AFDX-384, and pirenzepine. Methyllycaconitine administered systemically or intraperirhinally before acquisition impaired recognition memory tested after a 24-h, but not a 20-min delay. In contrast, all three muscarinic antagonists produced a similar, unusual pattern of impairment with amnesia after a 20-min delay, but remembrance after a 24-h delay. Thus, the amnesic effects of nicotinic and muscarinic antagonism were doubly dissociated across the 20-min and 24-h delays. The same pattern of shorter-term but not longer-term memory impairment was found for scopolamine whether the object preference test was carried out in a square arena or a Y-maze and whether rats of the Dark Agouti or Lister-hooded strains were used. Coinfusion of MLA and either scopolamine or AFDX-384 produced an impairment profile matching that for MLA. Hence, the antagonists did not act additively when coadministered. These findings establish an important role in recognition memory for both nicotinic and muscarinic cholinergic receptors in perirhinal cortex, and provide a challenge to simple ideas about the role of cholinergic processes in recognition memory: The effects of muscarinic and nicotinic antagonism are neither independent nor additive. PMID:21693636

  8. Differing time dependencies of object recognition memory impairments produced by nicotinic and muscarinic cholinergic antagonism in perirhinal cortex.

    PubMed

    Tinsley, Chris J; Fontaine-Palmer, Nadine S; Vincent, Maria; Endean, Emma P E; Aggleton, John P; Brown, Malcolm W; Warburton, E Clea

    2011-01-01

    The roles of muscarinic and nicotinic cholinergic receptors in perirhinal cortex in object recognition memory were compared. Rats' discrimination of a novel object preference test (NOP) test was measured after either systemic or local infusion into the perirhinal cortex of the nicotinic receptor antagonist methyllycaconitine (MLA), which targets alpha-7 (α7) amongst other nicotinic receptors or the muscarinic receptor antagonists scopolamine, AFDX-384, and pirenzepine. Methyllycaconitine administered systemically or intraperirhinally before acquisition impaired recognition memory tested after a 24-h, but not a 20-min delay. In contrast, all three muscarinic antagonists produced a similar, unusual pattern of impairment with amnesia after a 20-min delay, but remembrance after a 24-h delay. Thus, the amnesic effects of nicotinic and muscarinic antagonism were doubly dissociated across the 20-min and 24-h delays. The same pattern of shorter-term but not longer-term memory impairment was found for scopolamine whether the object preference test was carried out in a square arena or a Y-maze and whether rats of the Dark Agouti or Lister-hooded strains were used. Coinfusion of MLA and either scopolamine or AFDX-384 produced an impairment profile matching that for MLA. Hence, the antagonists did not act additively when coadministered. These findings establish an important role in recognition memory for both nicotinic and muscarinic cholinergic receptors in perirhinal cortex, and provide a challenge to simple ideas about the role of cholinergic processes in recognition memory: The effects of muscarinic and nicotinic antagonism are neither independent nor additive.

  9. Understanding eye movements in face recognition using hidden Markov models.

    PubMed

    Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

    2014-09-16

    We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

  10. Memory consolidation and expression of object recognition are susceptible to retroactive interference.

    PubMed

    Villar, María Eugenia; Martinez, María Cecilia; Lopes da Cunha, Pamela; Ballarini, Fabricio; Viola, Haydee

    2017-02-01

    With the aim of analyzing if object recognition long-term memory (OR-LTM) formation is susceptible to retroactive interference (RI), we submitted rats to sequential sample sessions using the same arena but changing the identity of a pair of objects placed in it. Separate groups of animals were tested in the arena in order to evaluate the LTM for these objects. Our results suggest that OR-LTM formation was retroactively interfered within a critical time window by the exploration of a new, but not familiar, object. This RI acted on the consolidation of the object explored in the first sample session because its OR-STM measured 3h after training was not affected, whereas the OR-LTM measured at 24h was impaired. This sample session also impaired the expression of OR memory when it took place before the test. Moreover, local inactivation of the dorsal Hippocampus (Hp) or the medial Prefrontal Cortex (mPFC) previous to the exploration of the second pair of objects impaired their consolidation restoring the LTM for the objects explored in the first session. This data suggests that both brain regions are involved in the processing of OR-memory and also that if those regions are engaged in another process before finishing the first consolidation process its LTM will be impaired by RI. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Physical Exercise During Adolescence Versus Adulthood: Differential Effects on Object Recognition Memory and BDNF Levels

    PubMed Central

    Hopkins, Michael E.; Nitecki, Roni; Bucci, David J.

    2011-01-01

    It is well established that physical exercise can enhance hippocampal-dependent forms of learning and memory in laboratory animals, commensurate with increases in hippocampal neural plasticity (BDNF mRNA/protein, neurogenesis, LTP). However, very little is known about the effects of exercise on other, non-spatial forms of learning and memory. In addition, there has been little investigation of the duration of the effects of exercise on behavior or plasticity. Likewise, few studies have compared the effects of exercising during adulthood versus adolescence. This is particularly important since exercise may capitalize on the peak of neural plasticity observed during adolescence, resulting in a different pattern of behavioral and neurobiological effects. The present study addressed these gaps in the literature by comparing the effects of 4 weeks of voluntary exercise (wheel running) during adulthood or adolescence on novel object recognition and BDNF levels in the perirhinal cortex (PER) and hippocampus (HP). Exercising during adulthood improved object recognition memory when rats were tested immediately after 4 weeks of exercise, an effect that was accompanied by increased BDNF levels in PER and HP. When rats were tested again 2 weeks after exercise ended, the effects of exercise on recognition memory and BDNF levels were no longer present. Exercising during adolescence had a very different pattern of effects. First, both exercising and non-exercising rats could discriminate between novel and familiar objects immediately after the exercise regimen ended; furthermore there was no group difference in BDNF levels. Two or four weeks later, however, rats that had previously exercised as adolescents could still discriminate between novel and familiar objects, while non-exercising rats could not. Moreover, the formerly exercising rats exhibited higher levels of BDNF in PER compared to HP, while the reverse was true in the non-exercising rats. These findings reveal a novel

  12. The role of line junctions in object recognition: The case of reading musical notation.

    PubMed

    Wong, Yetta Kwailing; Wong, Alan C-N

    2018-04-30

    Previous work has shown that line junctions are informative features for visual perception of objects, letters, and words. However, the sources of such sensitivity and their generalizability to other object categories are largely unclear. We addressed these questions by studying perceptual expertise in reading musical notation, a domain in which individuals with different levels of expertise are readily available. We observed that removing line junctions created by the contact between musical notes and staff lines selectively impaired recognition performance in experts and intermediate readers, but not in novices. The degree of performance impairment was predicted by individual fluency in reading musical notation. Our findings suggest that line junctions provide diagnostic information about object identity across various categories, including musical notation. However, human sensitivity to line junctions does not readily transfer from familiar to unfamiliar object categories, and has to be acquired through perceptual experience with the specific objects.

  13. Recognition of 3-D symmetric objects from range images in automated assembly tasks

    NASA Technical Reports Server (NTRS)

    Alvertos, Nicolas; Dcunha, Ivan

    1990-01-01

    A new technique is presented for the three dimensional recognition of symmetric objects from range images. Beginning from the implicit representation of quadrics, a set of ten coefficients is determined for symmetric objects like spheres, cones, cylinders, ellipsoids, and parallelepipeds. Instead of using these ten coefficients trying to fit them to smooth surfaces (patches) based on the traditional way of determining curvatures, a new approach based on two dimensional geometry is used. For each symmetric object, a unique set of two dimensional curves is obtained from the various angles at which the object is intersected with a plane. Using the same ten coefficients obtained earlier and based on the discriminant method, each of these curves is classified as a parabola, circle, ellipse, or hyperbola. Each symmetric object is found to possess a unique set of these two dimensional curves whereby it can be differentiated from the others. It is shown that instead of using the three dimensional discriminant which involves evaluation of the rank of its matrix, it is sufficient to use the two dimensional discriminant which only requires three arithmetic operations.

  14. Neuritin reverses deficits in murine novel object associative recognition memory caused by exposure to extremely low-frequency (50 Hz) electromagnetic fields.

    PubMed

    Zhao, Qian-Ru; Lu, Jun-Mei; Yao, Jin-Jing; Zhang, Zheng-Yu; Ling, Chen; Mei, Yan-Ai

    2015-07-03

    Animal studies have shown that electromagnetic field exposure may interfere with the activity of brain cells, thereby generating behavioral and cognitive disturbances. However, the underlying mechanisms and possible preventions are still unknown. In this study, we used a mouse model to examine the effects of exposure to extremely low-frequency (50 Hz) electromagnetic fields (ELF MFs) on a recognition memory task and morphological changes of hippocampal neurons. The data showed that ELF MFs exposure (1 mT, 12 h/day) induced a time-dependent deficit in novel object associative recognition memory and also decreased hippocampal dendritic spine density. This effect was observed without corresponding changes in spontaneous locomotor activity and was transient, which has only been seen after exposing mice to ELF MFs for 7-10 days. The over-expression of hippocampal neuritin, an activity-dependent neurotrophic factor, using an adeno-associated virus (AAV) vector significantly increased the neuritin level and dendritic spine density. This increase was paralleled with ELF MFs exposure-induced deficits in recognition memory and reductions of dendritic spine density. Collectively, our study provides evidence for the association between ELF MFs exposure, impairment of recognition memory, and resulting changes in hippocampal dendritic spine density. Neuritin prevented this ELF MFs-exposure-induced effect by increasing the hippocampal spine density.

  15. Segment-based acoustic models for continuous speech recognition

    NASA Astrophysics Data System (ADS)

    Ostendorf, Mari; Rohlicek, J. R.

    1993-07-01

    This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

  16. Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

    NASA Astrophysics Data System (ADS)

    Cyganek, Boguslaw; Smolka, Bogdan

    2015-02-01

    In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

  17. Recognition ROCS Are Curvilinear--Or Are They? On Premature Arguments against the Two-High-Threshold Model of Recognition

    ERIC Educational Resources Information Center

    Broder, Arndt; Schutz, Julia

    2009-01-01

    Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…

  18. Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

    NASA Astrophysics Data System (ADS)

    Yevin, Igor; Koblyakov, Alexander

    The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

  19. Object recognition and localization from 3D point clouds by maximum-likelihood estimation

    NASA Astrophysics Data System (ADS)

    Dantanarayana, Harshana G.; Huntley, Jonathan M.

    2017-08-01

    We present an algorithm based on maximum-likelihood analysis for the automated recognition of objects, and estimation of their pose, from 3D point clouds. Surfaces segmented from depth images are used as the features, unlike `interest point'-based algorithms which normally discard such data. Compared to the 6D Hough transform, it has negligible memory requirements, and is computationally efficient compared to iterative closest point algorithms. The same method is applicable to both the initial recognition/pose estimation problem as well as subsequent pose refinement through appropriate choice of the dispersion of the probability density functions. This single unified approach therefore avoids the usual requirement for different algorithms for these two tasks. In addition to the theoretical description, a simple 2 degrees of freedom (d.f.) example is given, followed by a full 6 d.f. analysis of 3D point cloud data from a cluttered scene acquired by a projected fringe-based scanner, which demonstrated an RMS alignment error as low as 0.3 mm.

  20. Cognitive enhancement effects of Bacopa monnieri (Brahmi) on novel object recognition and neuronal density in the prefrontal cortex, striatum and hippocampus in sub-chronic phencyclidine administration rat model of schizophrenia.

    PubMed

    Wetchateng, Thanitsara; Piyabhan, Pritsana

    2015-03-01

    Cognitive deficit is a significant problem, which finally occurs in all schizophrenic patients. It can not be attenuated by any antipsychotic drugs. It is well known that changes of neuronal density are correlated with learning and memory deficits. Bacopa monnieri (Brahmi), popularly known as a cognitive enhancer; might be a novel therapeutic agentfor cognitive deficit in schizophrenia by changing cerebral neuronal density. The objective of this study was to determine the effects of Brahmi on attenuation at cognitive deficit and on the neuronal density in the prefrontal cortex, striatum and cornu ammonis subfield 1 (CA1) and 2/3 (CA2/3) of hippocampus in sub-chronic phencyclidine (PCP) rat model of schizophrenia. Rats were assigned to three groups; Group-1: Control, Group-2: PCP administration and Group-3: PCP + Brahmi. Rats were testedfor cognitive ability by using the novel object recognition test. Neuronal density from a serial Nissl stain sections ofthe prefrontal cortex, striatum and hippocampus ofrat model ofschizophrenia were measured by using Image ProPlus software and manual counting. Sub-chronic administration of PCP results in cognitive deficits in novel object recognition task. This occurred alongside significantly increased neuronal density in CA1. The cognitive deficit was recovery to normal in PCP + Brahmi group and it occurred alongside significantly decreased neuronal density in CA1. On the other hand, significantly increased neuronal density was observed in CA2/3 of PCP + Brahmi group compared with PCP alone. Brahmi is a potential cognitive enhancer against schizophrenia. It reduces neuronal density, most likely glutamatergic neuron, which results in neuronal toxicity and cognitive deficit. Therefore, Brahmi has cognitive enhancement effect by reducing glutamatergic neuron in CAI. Moreover, it also has neurogenesis effect in CA2/3, which is needed to be investigated in the further study.

  1. Direction of Magnetoencephalography Sources Associated with Feedback and Feedforward Contributions in a Visual Object Recognition Task

    PubMed Central

    Ahlfors, Seppo P.; Jones, Stephanie R.; Ahveninen, Jyrki; Hämäläinen, Matti S.; Belliveau, John W.; Bar, Moshe

    2014-01-01

    Identifying inter-area communication in terms of the hierarchical organization of functional brain areas is of considerable interest in human neuroimaging. Previous studies have suggested that the direction of magneto- and electroencephalography (MEG, EEG) source currents depends on the layer-specific input patterns into a cortical area. We examined the direction in MEG source currents in a visual object recognition experiment in which there were specific expectations of activation in the fusiform region being driven by either feedforward or feedback inputs. The source for the early non-specific visual evoked response, presumably corresponding to feedforward driven activity, pointed outward, i.e., away from the white matter. In contrast, the source for the later, object-recognition related signals, expected to be driven by feedback inputs, pointed inward, toward the white matter. Associating specific features of the MEG/EEG source waveforms to feedforward and feedback inputs could provide unique information about the activation patterns within hierarchically organized cortical areas. PMID:25445356

  2. A dynamical pattern recognition model of gamma activity in auditory cortex

    PubMed Central

    Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

    2012-01-01

    This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

  3. Character recognition using a neural network model with fuzzy representation

    NASA Technical Reports Server (NTRS)

    Tavakoli, Nassrin; Seniw, David

    1992-01-01

    The degree to which digital images are recognized correctly by computerized algorithms is highly dependent upon the representation and the classification processes. Fuzzy techniques play an important role in both processes. In this paper, the role of fuzzy representation and classification on the recognition of digital characters is investigated. An experimental Neural Network model with application to character recognition was developed. Through a set of experiments, the effect of fuzzy representation on the recognition accuracy of this model is presented.

  4. Testing a Neurocomputational Model of Recollection, Familiarity, and Source Recognition

    ERIC Educational Resources Information Center

    Elfman, Kane W.; Parks, Colleen M.; Yonelinas, Andrew P.

    2008-01-01

    The authors assess whether the complementary learning systems model of the medial temporal lobes (Norman & O'Reilly, 2003) is able to account for source recognition receiver operating characteristics (ROCs). The model assumes that recognition reflects the contribution of a hippocampally mediated recollection process and a cortically mediated…

  5. Atoms of recognition in human and computer vision.

    PubMed

    Ullman, Shimon; Assif, Liav; Fetaya, Ethan; Harari, Daniel

    2016-03-08

    Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have shown remarkable progress and have begun to rival human performance in some challenging tasks. These models are trained on image examples and learn to extract features and representations and to use them for categorization. It remains unclear, however, whether the representations and learning processes discovered by current models are similar to those used by the human visual system. Here we show, by introducing and using minimal recognizable images, that the human visual system uses features and processes that are not used by current models and that are critical for recognition. We found by psychophysical studies that at the level of minimal recognizable images a minute change in the image can have a drastic effect on recognition, thus identifying features that are critical for the task. Simulations then showed that current models cannot explain this sensitivity to precise feature configurations and, more generally, do not learn to recognize minimal images at a human level. The role of the features shown here is revealed uniquely at the minimal level, where the contribution of each feature is essential. A full understanding of the learning and use of such features will extend our understanding of visual recognition and its cortical mechanisms and will enhance the capacity of computational models to learn from visual experience and to deal with recognition and detailed image interpretation.

  6. Neuropeptide S enhances memory and mitigates memory impairment induced by MK801, scopolamine or Aβ₁₋₄₂ in mice novel object and object location recognition tasks.

    PubMed

    Han, Ren-Wen; Zhang, Rui-San; Xu, Hong-Jiao; Chang, Min; Peng, Ya-Li; Wang, Rui

    2013-07-01

    Neuropeptide S (NPS), the endogenous ligand of NPSR, has been shown to promote arousal and anxiolytic-like effects. According to the predominant distribution of NPSR in brain tissues associated with learning and memory, NPS has been reported to modulate cognitive function in rodents. Here, we investigated the role of NPS in memory formation, and determined whether NPS could mitigate memory impairment induced by selective N-methyl-D-aspartate receptor antagonist MK801, muscarinic cholinergic receptor antagonist scopolamine or Aβ₁₋₄₂ in mice, using novel object and object location recognition tasks. Intracerebroventricular (i.c.v.) injection of 1 nmol NPS 5 min after training not only facilitated object recognition memory formation, but also prolonged memory retention in both tasks. The improvement of object recognition memory induced by NPS could be blocked by the selective NPSR antagonist SHA 68, indicating pharmacological specificity. Then, we found that i.c.v. injection of NPS reversed memory disruption induced by MK801, scopolamine or Aβ₁₋₄₂ in both tasks. In summary, our results indicate that NPS facilitates memory formation and prolongs the retention of memory through activation of the NPSR, and mitigates amnesia induced by blockage of glutamatergic or cholinergic system or by Aβ₁₋₄₂, suggesting that NPS/NPSR system may be a new target for enhancing memory and treating amnesia. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. D-Serine and a glycine transporter inhibitor improve MK-801-induced cognitive deficits in a novel object recognition test in rats.

    PubMed

    Karasawa, Jun-Ichi; Hashimoto, Kenji; Chaki, Shigeyuki

    2008-01-10

    Compounds enhancing N-methyl-d-aspartate (NMDA) glutamate receptor function have been reported to improve cognitive deficits. Since cognitive deficits are considered to be the core symptom of schizophrenia, enhancing NMDA receptor function represents a promising approach to treating schizophrenia. In the present study, we investigated whether d-serine or a glycine transporter inhibitor N-[3-(4'-fluorophenyl)-3-(4'-phenylphenoxy)propyl]sarcosine (NFPS), both of which enhance NMDA receptor function, could improve MK-801-induced cognitive deficits in rats, and compared their effects with those of the atypical antipsychotic clozapine and of the typical antipsychotic haloperidol. To assess cognitive function, we used a novel object recognition test in rats that measured spontaneous exploratory activity of a novel object when paired with a familiar object. We then evaluated the effects of the compounds on cognitive deficits induced by treatment with MK-801, the NMDA receptor antagonist. Pretreatment with clozapine (1, 5 mg/kg, i.p.) but not haloperidol (0.03, 0.1 mg/kg, i.p.) significantly improved MK-801-induced cognitive deficits. Pretreatment with D-serine at 800 mg/kg (i.p.) or NFPS (0.3, 1 mg/kg, i.p.) significantly improved MK-801-induced cognitive deficits under this test paradigm. These findings suggest that impaired preference for novel objects induced by MK-801 in the novel object recognition test could be a useful animal model for evaluating the efficacy of compounds targeting the cognitive deficits observed in schizophrenic patients. The results also suggest that enhancing NMDA receptor function is an effective way for treating the cognitive deficits associated with schizophrenia.

  8. Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition

    PubMed Central

    Burns, Edwin J.; Tree, Jeremy J.; Weidemann, Christoph T.

    2014-01-01

    Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct “remember” responses and more false alarms than controls. EEG results showed that posterior “remember” old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior “know” old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal “know” old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects. PMID:25177283

  9. The Complex Action Recognition via the Correlated Topic Model

    PubMed Central

    Tu, Hong-bin; Xia, Li-min; Wang, Zheng-wu

    2014-01-01

    Human complex action recognition is an important research area of the action recognition. Among various obstacles to human complex action recognition, one of the most challenging is to deal with self-occlusion, where one body part occludes another one. This paper presents a new method of human complex action recognition, which is based on optical flow and correlated topic model (CTM). Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms of an occlusion state variable. Secondly, the structure from motion (SFM) is used for reconstructing the missing data of point trajectories. Then, we can extract the key frame based on motion feature from optical flow and the ratios of the width and height are extracted by the human silhouette. Finally, we use the topic model of correlated topic model (CTM) to classify action. Experiments were performed on the KTH, Weizmann, and UIUC action dataset to test and evaluate the proposed method. The compared experiment results showed that the proposed method was more effective than compared methods. PMID:24574920

  10. Unsupervised object segmentation with a hybrid graph model (HGM).

    PubMed

    Liu, Guangcan; Lin, Zhouchen; Yu, Yong; Tang, Xiaoou

    2010-05-01

    In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmentation can be regarded as a special data clustering problem where both class-specific information and local texture/color similarities have to be considered. To this end, we propose a hybrid graph model (HGM) that can make effective use of both symmetric and asymmetric relationship among samples. The vertices of a hybrid graph represent the samples and are connected by directed edges and/or undirected ones, which represent the asymmetric and/or symmetric relationship between them, respectively. When applied to object segmentation, vertices are superpixels, the asymmetric relationship is the conditional dependence of occurrence, and the symmetric relationship is the color/texture similarity. By combining the Markov chain formed by the directed subgraph and the minimal cut of the undirected subgraph, the object boundaries can be determined for each image. Using the HGM, we can conveniently achieve simultaneous segmentation and recognition by integrating both top-down and bottom-up information into a unified process. Experiments on 42 object classes (9,415 images in total) show promising results.

  11. Bridging automatic speech recognition and psycholinguistics: Extending Shortlist to an end-to-end model of human speech recognition (L)

    NASA Astrophysics Data System (ADS)

    Scharenborg, Odette; ten Bosch, Louis; Boves, Lou; Norris, Dennis

    2003-12-01

    This letter evaluates potential benefits of combining human speech recognition (HSR) and automatic speech recognition by building a joint model of an automatic phone recognizer (APR) and a computational model of HSR, viz., Shortlist [Norris, Cognition 52, 189-234 (1994)]. Experiments based on ``real-life'' speech highlight critical limitations posed by some of the simplifying assumptions made in models of human speech recognition. These limitations could be overcome by avoiding hard phone decisions at the output side of the APR, and by using a match between the input and the internal lexicon that flexibly copes with deviations from canonical phonemic representations.

  12. Optical Pattern Recognition

    NASA Astrophysics Data System (ADS)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

    Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

  13. Coding of visual object features and feature conjunctions in the human brain.

    PubMed

    Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

    2008-01-01

    Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

  14. [NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data].

    PubMed

    Wang, Yan; Tian, Qing-Jiu; Huang, Yan; Wei, Hong-Wei

    2013-04-01

    The present paper takes Chuzhou in Anhui Province as the research area, and deciduous broad-leaved forest as the research object. Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bearing, and the model was applied to HJ-CCD remote sensing image on April 1, 2012 and May 4, 2012. At last, the spatial distribution map of deciduous broad-leaved forest was extracted effectively, and the results of extraction were verified and evaluated. The result shows the validity of NDVI difference rate extraction method proposed in this paper and also verifies the applicability of using HJ-CCD data for vegetation classification and recognition.

  15. Automatic recognition of ship types from infrared images using superstructure moment invariants

    NASA Astrophysics Data System (ADS)

    Li, Heng; Wang, Xinyu

    2007-11-01

    Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.

  16. Fuzzy object modeling

    NASA Astrophysics Data System (ADS)

    Udupa, Jayaram K.; Odhner, Dewey; Falcao, Alexandre X.; Ciesielski, Krzysztof C.; Miranda, Paulo A. V.; Vaideeswaran, Pavithra; Mishra, Shipra; Grevera, George J.; Saboury, Babak; Torigian, Drew A.

    2011-03-01

    To make Quantitative Radiology (QR) a reality in routine clinical practice, computerized automatic anatomy recognition (AAR) becomes essential. As part of this larger goal, we present in this paper a novel fuzzy strategy for building bodywide group-wise anatomic models. They have the potential to handle uncertainties and variability in anatomy naturally and to be integrated with the fuzzy connectedness framework for image segmentation. Our approach is to build a family of models, called the Virtual Quantitative Human, representing normal adult subjects at a chosen resolution of the population variables (gender, age). Models are represented hierarchically, the descendents representing organs contained in parent organs. Based on an index of fuzziness of the models, 32 thorax data sets, and 10 organs defined in them, we found that the hierarchical approach to modeling can effectively handle the non-linear relationships in position, scale, and orientation that exist among organs in different patients.

  17. Improving language models for radiology speech recognition.

    PubMed

    Paulett, John M; Langlotz, Curtis P

    2009-02-01

    Speech recognition systems have become increasingly popular as a means to produce radiology reports, for reasons both of efficiency and of cost. However, the suboptimal recognition accuracy of these systems can affect the productivity of the radiologists creating the text reports. We analyzed a database of over two million de-identified radiology reports to determine the strongest determinants of word frequency. Our results showed that body site and imaging modality had a similar influence on the frequency of words and of three-word phrases as did the identity of the speaker. These findings suggest that the accuracy of speech recognition systems could be significantly enhanced by further tailoring their language models to body site and imaging modality, which are readily available at the time of report creation.

  18. Modeling the effect of channel number and interaction on consonant recognition in a cochlear implant peak-picking strategy.

    PubMed

    Verschuur, Carl

    2009-03-01

    Difficulties in speech recognition experienced by cochlear implant users may be attributed both to information loss caused by signal processing and to information loss associated with the interface between the electrode array and auditory nervous system, including cross-channel interaction. The objective of the work reported here was to attempt to partial out the relative contribution of these different factors to consonant recognition. This was achieved by comparing patterns of consonant feature recognition as a function of channel number and presence/absence of background noise in users of the Nucleus 24 device with normal hearing subjects listening to acoustic models that mimicked processing of that device. Additionally, in the acoustic model experiment, a simulation of cross-channel spread of excitation, or "channel interaction," was varied. Results showed that acoustic model experiments were highly correlated with patterns of performance in better-performing cochlear implant users. Deficits to consonant recognition in this subgroup could be attributed to cochlear implant processing, whereas channel interaction played a much smaller role in determining performance errors. The study also showed that large changes to channel number in the Advanced Combination Encoder signal processing strategy led to no substantial changes in performance.

  19. Sex-specific effects of Cacna1c haploinsufficiency on object recognition, spatial memory, and reversal learning capabilities in rats.

    PubMed

    Braun, Moria D; Kisko, Theresa M; Vecchia, Débora Dalla; Andreatini, Roberto; Schwarting, Rainer K W; Wöhr, Markus

    2018-05-23

    The CACNA1C gene is strongly implicated in the etiology of multiple major neuropsychiatric disorders, such as bipolar disorder, major depression, and schizophrenia, with cognitive deficits being a common feature. It is unclear, however, by which mechanisms CACNA1C variants advance the risk of developing neuropsychiatric disorders. This study set out to investigate cognitive functioning in a newly developed genetic Cacna1c rat model. Specifically, spatial and reversal learning, as well as object recognition memory were assessed in heterozygous Cacna1c +/- rats and compared to wildtype Cacna1c +/+ littermate controls in both sexes. Our results show that both Cacna1c +/+ and Cacna1c +/- animals were able to learn the rewarded arm configuration of a radial maze over the course of seven days. Both groups also showed reversal learning patterns indicative of intact abilities. In females, genotype differences were evident in the initial spatial learning phase, with Cacna1c +/- females showing hypo-activity and fewer mixed errors. In males, a difference was found during probe trials for both learning phases, with Cacna1c +/- rats displaying better distinction between previously baited and non-baited arms; and regarding cognitive flexibility in favor of the Cacna1c +/+ animals. All experimental groups proved to be sensitive to reward magnitude and fully able to distinguish between novel and familiar objects in the novel object recognition task. Taken together, these results indicate that Cacna1c haploinsufficiency has a minor, but positive impact on (spatial) memory functions in rats. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Visual object recognition and tracking

    NASA Technical Reports Server (NTRS)

    Chang, Chu-Yin (Inventor); English, James D. (Inventor); Tardella, Neil M. (Inventor)

    2010-01-01

    This invention describes a method for identifying and tracking an object from two-dimensional data pictorially representing said object by an object-tracking system through processing said two-dimensional data using at least one tracker-identifier belonging to the object-tracking system for providing an output signal containing: a) a type of the object, and/or b) a position or an orientation of the object in three-dimensions, and/or c) an articulation or a shape change of said object in said three dimensions.

  1. Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework

    ERIC Educational Resources Information Center

    Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A.

    2012-01-01

    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…

  2. Object-Place Recognition Learning Triggers Rapid Induction of Plasticity-Related Immediate Early Genes and Synaptic Proteins in the Rat Dentate Gyrus

    PubMed Central

    Soulé, Jonathan; Penke, Zsuzsa; Kanhema, Tambudzai; Alme, Maria Nordheim; Laroche, Serge; Bramham, Clive R.

    2008-01-01

    Long-term recognition memory requires protein synthesis, but little is known about the coordinate regulation of specific genes. Here, we examined expression of the plasticity-associated immediate early genes (Arc, Zif268, and Narp) in the dentate gyrus following long-term object-place recognition learning in rats. RT-PCR analysis from dentate gyrus tissue collected shortly after training did not reveal learning-specific changes in Arc mRNA expression. In situ hybridization and immunohistochemistry were therefore used to assess possible sparse effects on gene expression. Learning about objects increased the density of granule cells expressing Arc, and to a lesser extent Narp, specifically in the dorsal blade of the dentate gyrus, while Zif268 expression was elevated across both blades. Thus, object-place recognition triggers rapid, blade-specific upregulation of plasticity-associated immediate early genes. Furthermore, Western blot analysis of dentate gyrus homogenates demonstrated concomitant upregulation of three postsynaptic density proteins (Arc, PSD-95, and α-CaMKII) with key roles in long-term synaptic plasticity and long-term memory. PMID:19190776

  3. The Memory State Heuristic: A Formal Model Based on Repeated Recognition Judgments

    ERIC Educational Resources Information Center

    Castela, Marta; Erdfelder, Edgar

    2017-01-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e.,…

  4. A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

    PubMed

    Yuan, Tao; Zheng, Xinqi; Hu, Xuan; Zhou, Wei; Wang, Wei

    2014-01-01

    Objective and effective image quality assessment (IQA) is directly related to the application of optical remote sensing images (ORSI). In this study, a new IQA method of standardizing the target object recognition rate (ORR) is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

  5. Excess influx of Zn(2+) into dentate granule cells affects object recognition memory via attenuated LTP.

    PubMed

    Suzuki, Miki; Fujise, Yuki; Tsuchiya, Yuka; Tamano, Haruna; Takeda, Atsushi

    2015-08-01

    The influx of extracellular Zn(2+) into dentate granule cells is nonessential for dentate gyrus long-term potentiation (LTP) and the physiological significance of extracellular Zn(2+) dynamics is unknown in the dentate gyrus. Excess increase in extracellular Zn(2+) in the hippocampal CA1, which is induced with excitation of zincergic neurons, induces memory deficit via excess influx of Zn(2+) into CA1 pyramidal cells. In the present study, it was examined whether extracellular Zn(2+) induces object recognition memory deficit via excess influx of Zn(2+) into dentate granule cells. KCl (100 mM, 2 µl) was locally injected into the dentate gyrus. The increase in intracellular Zn(2+) in dentate granule cells induced with high K(+) was blocked by co-injection of CaEDTA and CNQX, an extracellular Zn(2+) chelator and an AMPA receptor antagonist, respectively, suggesting that high K(+) increases the influx of Zn(2+) into dentate granule cells via AMPA receptor activation. Dentate gyrus LTP induction was attenuated 1 h after KCl injection into the dentate gyrus and also attenuated when KCl was injected 5 min after the induction. Memory deficit was induced when training of object recognition test was performed 1 h after KCl injection into the dentate gyrus and also induced when KCl was injected 5 min after the training. High K(+)-induced impairments of LTP and memory were rescued by co-injection of CaEDTA. These results indicate that excess influx of Zn(2+) into dentate granule cells via AMPA receptor activation affects object recognition memory via attenuated LTP induction. Even in the dentate gyrus where is scarcely innervated by zincergic neurons, it is likely that extracellular Zn(2+) homeostasis is strictly regulated for cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Exploring Biomolecular Recognition by Modeling and Simulation

    NASA Astrophysics Data System (ADS)

    Wade, Rebecca

    2007-12-01

    Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

  7. Emerging technologies with potential for objectively evaluating speech recognition skills.

    PubMed

    Rawool, Vishakha Waman

    2016-01-01

    Work-related exposure to noise and other ototoxins can cause damage to the cochlea, synapses between the inner hair cells, the auditory nerve fibers, and higher auditory pathways, leading to difficulties in recognizing speech. Procedures designed to determine speech recognition scores (SRS) in an objective manner can be helpful in disability compensation cases where the worker claims to have poor speech perception due to exposure to noise or ototoxins. Such measures can also be helpful in determining SRS in individuals who cannot provide reliable responses to speech stimuli, including patients with Alzheimer's disease, traumatic brain injuries, and infants with and without hearing loss. Cost-effective neural monitoring hardware and software is being rapidly refined due to the high demand for neurogaming (games involving the use of brain-computer interfaces), health, and other applications. More specifically, two related advances in neuro-technology include relative ease in recording neural activity and availability of sophisticated analysing techniques. These techniques are reviewed in the current article and their applications for developing objective SRS procedures are proposed. Issues related to neuroaudioethics (ethics related to collection of neural data evoked by auditory stimuli including speech) and neurosecurity (preservation of a person's neural mechanisms and free will) are also discussed.

  8. Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

    PubMed

    Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

    2015-10-01

    Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published

  9. Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

    PubMed

    Lee, Jong-Seok; Park, Cheol Hoon

    2010-08-01

    We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

  10. Invariant recognition drives neural representations of action sequences

    PubMed Central

    Poggio, Tomaso

    2017-01-01

    Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

  11. Visual Object Recognition and Tracking of Tools

    NASA Technical Reports Server (NTRS)

    English, James; Chang, Chu-Yin; Tardella, Neil

    2011-01-01

    A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images

  12. Restoration of Dopamine Release Deficits during Object Recognition Memory Acquisition Attenuates Cognitive Impairment in a Triple Transgenic Mice Model of Alzheimer's Disease

    ERIC Educational Resources Information Center

    Guzman-Ramos, Kioko; Moreno-Castilla, Perla; Castro-Cruz, Monica; McGaugh, James L.; Martinez-Coria, Hilda; LaFerla, Frank M.; Bermudez-Rattoni, Federico

    2012-01-01

    Previous findings indicate that the acquisition and consolidation of recognition memory involves dopaminergic activity. Although dopamine deregulation has been observed in Alzheimer's disease (AD) patients, the dysfunction of this neurotransmitter has not been investigated in animal models of AD. The aim of this study was to assess, by in vivo…

  13. Recognition of partially occluded threat objects using the annealed Hopefield network

    NASA Technical Reports Server (NTRS)

    Kim, Jung H.; Yoon, Sung H.; Park, Eui H.; Ntuen, Celestine A.

    1992-01-01

    Recognition of partially occluded objects has been an important issue to airport security because occlusion causes significant problems in identifying and locating objects during baggage inspection. The neural network approach is suitable for the problems in the sense that the inherent parallelism of neural networks pursues many hypotheses in parallel resulting in high computation rates. Moreover, they provide a greater degree of robustness or fault tolerance than conventional computers. The annealed Hopfield network which is derived from the mean field annealing (MFA) has been developed to find global solutions of a nonlinear system. In the study, it has been proven that the system temperature of MFA is equivalent to the gain of the sigmoid function of a Hopfield network. In our early work, we developed the hybrid Hopfield network (HHN) for fast and reliable matching. However, HHN doesn't guarantee global solutions and yields false matching under heavily occluded conditions because HHN is dependent on initial states by its nature. In this paper, we present the annealed Hopfield network (AHN) for occluded object matching problems. In AHN, the mean field theory is applied to the hybird Hopfield network in order to improve computational complexity of the annealed Hopfield network and provide reliable matching under heavily occluded conditions. AHN is slower than HHN. However, AHN provides near global solutions without initial restrictions and provides less false matching than HHN. In conclusion, a new algorithm based upon a neural network approach was developed to demonstrate the feasibility of the automated inspection of threat objects from x-ray images. The robustness of the algorithm is proved by identifying occluded target objects with large tolerance of their features.

  14. Optical character recognition of handwritten Arabic using hidden Markov models

    NASA Astrophysics Data System (ADS)

    Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

    2011-04-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

  15. Optical character recognition of handwritten Arabic using hidden Markov models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.

    2011-01-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language ismore » initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.« less

  16. Recognition of surgical skills using hidden Markov models

    NASA Astrophysics Data System (ADS)

    Speidel, Stefanie; Zentek, Tom; Sudra, Gunther; Gehrig, Tobias; Müller-Stich, Beat Peter; Gutt, Carsten; Dillmann, Rüdiger

    2009-02-01

    Minimally invasive surgery is a highly complex medical discipline and can be regarded as a major breakthrough in surgical technique. A minimally invasive intervention requires enhanced motor skills to deal with difficulties like the complex hand-eye coordination and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality techniques. To recognize and analyze the current situation for context-aware assistance, we need intraoperative sensor data and a model of the intervention. Characteristics of a situation are the performed activity, the used instruments, the surgical objects and the anatomical structures. Important information about the surgical activity can be acquired by recognizing the surgical gesture performed. Surgical gestures in minimally invasive surgery like cutting, knot-tying or suturing are here referred to as surgical skills. We use the motion data from the endoscopic instruments to classify and analyze the performed skill and even use it for skill evaluation in a training scenario. The system uses Hidden Markov Models (HMM) to model and recognize a specific surgical skill like knot-tying or suturing with an average recognition rate of 92%.

  17. Fast and flexible 3D object recognition solutions for machine vision applications

    NASA Astrophysics Data System (ADS)

    Effenberger, Ira; Kühnle, Jens; Verl, Alexander

    2013-03-01

    In automation and handling engineering, supplying work pieces between different stages along the production process chain is of special interest. Often the parts are stored unordered in bins or lattice boxes and hence have to be separated and ordered for feeding purposes. An alternative to complex and spacious mechanical systems such as bowl feeders or conveyor belts, which are typically adapted to the parts' geometry, is using a robot to grip the work pieces out of a bin or from a belt. Such applications are in need of reliable and precise computer-aided object detection and localization systems. For a restricted range of parts, there exists a variety of 2D image processing algorithms that solve the recognition problem. However, these methods are often not well suited for the localization of randomly stored parts. In this paper we present a fast and flexible 3D object recognizer that localizes objects by identifying primitive features within the objects. Since technical work pieces typically consist to a substantial degree of geometric primitives such as planes, cylinders and cones, such features usually carry enough information in order to determine the position of the entire object. Our algorithms use 3D best-fitting combined with an intelligent data pre-processing step. The capability and performance of this approach is shown by applying the algorithms to real data sets of different industrial test parts in a prototypical bin picking demonstration system.

  18. TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chang, X; Mazur, T; Yang, D

    Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformationmore » and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants

  19. Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

    PubMed

    Hilbig, Benjamin E; Pohl, Rüdiger F

    2009-09-01

    According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

  20. Neuritin reverses deficits in murine novel object associative recognition memory caused by exposure to extremely low-frequency (50 Hz) electromagnetic fields

    PubMed Central

    Zhao, Qian-Ru; Lu, Jun-Mei; Yao, Jin-Jing; Zhang, Zheng-Yu; Ling, Chen; Mei, Yan-Ai

    2015-01-01

    Animal studies have shown that electromagnetic field exposure may interfere with the activity of brain cells, thereby generating behavioral and cognitive disturbances. However, the underlying mechanisms and possible preventions are still unknown. In this study, we used a mouse model to examine the effects of exposure to extremely low-frequency (50 Hz) electromagnetic fields (ELF MFs) on a recognition memory task and morphological changes of hippocampal neurons. The data showed that ELF MFs exposure (1 mT, 12 h/day) induced a time-dependent deficit in novel object associative recognition memory and also decreased hippocampal dendritic spine density. This effect was observed without corresponding changes in spontaneous locomotor activity and was transient, which has only been seen after exposing mice to ELF MFs for 7-10 days. The over-expression of hippocampal neuritin, an activity-dependent neurotrophic factor, using an adeno-associated virus (AAV) vector significantly increased the neuritin level and dendritic spine density. This increase was paralleled with ELF MFs exposure-induced deficits in recognition memory and reductions of dendritic spine density. Collectively, our study provides evidence for the association between ELF MFs exposure, impairment of recognition memory, and resulting changes in hippocampal dendritic spine density. Neuritin prevented this ELF MFs-exposure-induced effect by increasing the hippocampal spine density. PMID:26138388

  1. Objects predict fixations better than early saliency.

    PubMed

    Einhäuser, Wolfgang; Spain, Merrielle; Perona, Pietro

    2008-11-20

    Humans move their eyes while looking at scenes and pictures. Eye movements correlate with shifts in attention and are thought to be a consequence of optimal resource allocation for high-level tasks such as visual recognition. Models of attention, such as "saliency maps," are often built on the assumption that "early" features (color, contrast, orientation, motion, and so forth) drive attention directly. We explore an alternative hypothesis: Observers attend to "interesting" objects. To test this hypothesis, we measure the eye position of human observers while they inspect photographs of common natural scenes. Our observers perform different tasks: artistic evaluation, analysis of content, and search. Immediately after each presentation, our observers are asked to name objects they saw. Weighted with recall frequency, these objects predict fixations in individual images better than early saliency, irrespective of task. Also, saliency combined with object positions predicts which objects are frequently named. This suggests that early saliency has only an indirect effect on attention, acting through recognized objects. Consequently, rather than treating attention as mere preprocessing step for object recognition, models of both need to be integrated.

  2. Constant Light Desynchronizes Olfactory versus Object and Visuospatial Recognition Memory Performance

    PubMed Central

    Tam, Shu K.E.; Hasan, Sibah; Brown, Laurence A.; Jagannath, Aarti; Hankins, Mark W.; Foster, Russell G.; Vyazovskiy, Vladyslav V.

    2017-01-01

    Circadian rhythms optimize physiology and behavior to the varying demands of the 24 h day. The master circadian clock is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and it regulates circadian oscillators in tissues throughout the body to prevent internal desynchrony. Here, we demonstrate for the first time that, under standard 12 h:12 h light/dark (LD) cycles, object, visuospatial, and olfactory recognition performance in C57BL/6J mice is consistently better at midday relative to midnight. However, under repeated exposure to constant light (rLL), recognition performance becomes desynchronized, with object and visuospatial performance better at subjective midday and olfactory performance better at subjective midnight. This desynchrony in behavioral performance is mirrored by changes in expression of the canonical clock genes Period1 and Period2 (Per1 and Per2), as well as the immediate-early gene Fos in the SCN, dorsal hippocampus, and olfactory bulb. Under rLL, rhythmic Per1 and Fos expression is attenuated in the SCN. In contrast, hippocampal gene expression remains rhythmic, mirroring object and visuospatial performance. Strikingly, Per1 and Fos expression in the olfactory bulb is reversed, mirroring the inverted olfactory performance. Temporal desynchrony among these regions does not result in arrhythmicity because core body temperature and exploratory activity rhythms persist under rLL. Our data provide the first demonstration that abnormal lighting conditions can give rise to temporal desynchrony between autonomous circadian oscillators in different regions, with different consequences for performance across different sensory domains. Such a dispersed network of dissociable circadian oscillators may provide greater flexibility when faced with conflicting environmental signals. SIGNIFICANCE STATEMENT A master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus regulates physiology and behavior across the 24 h day by

  3. A Temporally Distinct Role for Group I and Group II Metabotropic Glutamate Receptors in Object Recognition Memory

    ERIC Educational Resources Information Center

    Brown, Malcolm Watson; Warburton, Elizabeth Clea; Barker, Gareth Robert Isaac; Bashir, Zafar Iqbal

    2006-01-01

    Recognition memory, involving the ability to discriminate between a novel and familiar object, depends on the integrity of the perirhinal cortex (PRH). Glutamate, the main excitatory neurotransmitter in the cortex, is essential for many types of memory processes. Of the subtypes of glutamate receptor, metabotropic receptors (mGluRs) have received…

  4. Evidence for the Activation of Sensorimotor Information during Visual Word Recognition: The Body-Object Interaction Effect

    ERIC Educational Resources Information Center

    Siakaluk, Paul D.; Pexman, Penny M.; Aguilera, Laura; Owen, William J.; Sears, Christopher R.

    2008-01-01

    We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a word's referent. A set of high BOI words (e.g., "mask") and a set of low BOI…

  5. Intracerebroventricular oxytocin administration in rats enhances object recognition and increases expression of neurotrophins, microtubule-associated protein 2, and synapsin I.

    PubMed

    Havranek, Tomas; Zatkova, Martina; Lestanova, Zuzana; Bacova, Zuzana; Mravec, Boris; Hodosy, Julius; Strbak, Vladimir; Bakos, Jan

    2015-06-01

    Brain oxytocin regulates a variety of social and affiliative behaviors and affects also learning and memory. However, mechanisms of its action at the level of neuronal circuits are not fully understood. The present study tests the hypothesis that molecular factors required for memory formation and synaptic plasticity, including brain-derived neurotrophic factor, neural growth factor, nestin, microtubule-associated protein 2 (MAP2), and synapsin I, are enhanced by central administration of oxytocin. We also investigated whether oxytocin enhances object recognition and acts as anxiolytic agent. Therefore, male Wistar rats were infused continuously with oxytocin (20 ng/µl) via an osmotic minipump into the lateral cerebral ventricle for 7 days; controls were infused with vehicle. The object recognition test, open field test, and elevated plus maze test were performed on the sixth, seventh, and eighth days from starting the infusion. No significant effects of oxytocin on anxious-like behavior were observed. The object recognition test showed that oxytocin-treated rats significantly preferred unknown objects. Oxytocin treatment significantly increased gene expression and protein levels of neurotrophins, MAP2, and synapsin I in the hippocampus. No changes were observed in nestin expression. Our results provide the first direct evidence implicating oxytocin as a regulator of brain plasticity at the level of changes of neuronal growth factors, cytoskeletal proteins, and behavior. The data support assumption that oxytocin is important for short-term hippocampus-dependent memory. © 2015 Wiley Periodicals, Inc.

  6. Learning to distinguish similar objects

    NASA Astrophysics Data System (ADS)

    Seibert, Michael; Waxman, Allen M.; Gove, Alan N.

    1995-04-01

    This paper describes how the similarities and differences among similar objects can be discovered during learning to facilitate recognition. The application domain is single views of flying model aircraft captured in silhouette by a CCD camera. The approach was motivated by human psychovisual and monkey neurophysiological data. The implementation uses neural net processing mechanisms to build a hierarchy that relates similar objects to superordinate classes, while simultaneously discovering the salient differences between objects within a class. Learning and recognition experiments both with and without the class similarity and difference learning show the effectiveness of the approach on this visual data. To test the approach, the hierarchical approach was compared to a non-hierarchical approach, and was found to improve the average percentage of correctly classified views from 77% to 84%.

  7. Estradiol-induced object recognition memory consolidation is dependent on activation of mTOR signaling in the dorsal hippocampus

    PubMed Central

    Fortress, Ashley M.; Fan, Lu; Orr, Patrick T.; Zhao, Zaorui; Frick, Karyn M.

    2013-01-01

    The mammalian target of rapamycin (mTOR) signaling pathway is an important regulator of protein synthesis and is essential for various forms of hippocampal memory. Here, we asked whether the enhancement of object recognition memory consolidation produced by dorsal hippocampal infusion of 17β-estradiol (E2) is dependent on mTOR signaling in the dorsal hippocampus, and whether E2-induced mTOR signaling is dependent on dorsal hippocampal phosphatidylinositol 3-kinase (PI3K) and extracellular signal-regulated kinase (ERK) activation. We first demonstrated that the enhancement of object recognition induced by E2 was blocked by dorsal hippocampal inhibition of ERK, PI3K, or mTOR activation. We then showed that an increase in dorsal hippocampal ERK phosphorylation 5 min after intracerebroventricular (ICV) E2 infusion was also blocked by dorsal hippocampal infusion of the three cell signaling inhibitors. Next, we found that ICV infusion of E2 increased phosphorylation of the downstream mTOR targets S6K (Thr-421) and 4E-BP1 in the dorsal hippocampus 5 min after infusion, and that this phosphorylation was blocked by dorsal hippocampal infusion of inhibitors of ERK, PI3K, and mTOR. Collectively, these data demonstrate for the first time that activation of the dorsal hippocampal mTOR signaling pathway is necessary for E2 to enhance object recognition memory consolidation and that E2-induced mTOR activation is dependent on upstream activation of ERK and PI3K signaling. PMID:23422279

  8. Neural dynamics of object-based multifocal visual spatial attention and priming: Object cueing, useful-field-of-view, and crowding

    PubMed Central

    Foley, Nicholas C.; Grossberg, Stephen; Mingolla, Ennio

    2015-01-01

    How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how “attentional shrouds” are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of

  9. Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

    PubMed

    Foley, Nicholas C; Grossberg, Stephen; Mingolla, Ennio

    2012-08-01

    How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how "attentional shrouds" are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of

  10. Generation, recognition, and consistent fusion of partial boundary representations from range images

    NASA Astrophysics Data System (ADS)

    Kohlhepp, Peter; Hanczak, Andrzej M.; Li, Gang

    1994-10-01

    This paper presents SOMBRERO, a new system for recognizing and locating 3D, rigid, non- moving objects from range data. The objects may be polyhedral or curved, partially occluding, touching or lying flush with each other. For data collection, we employ 2D time- of-flight laser scanners mounted to a moving gantry robot. By combining sensor and robot coordinates, we obtain 3D cartesian coordinates. Boundary representations (Brep's) provide view independent geometry models that are both efficiently recognizable and derivable automatically from sensor data. SOMBRERO's methods for generating, matching and fusing Brep's are highly synergetic. A split-and-merge segmentation algorithm with dynamic triangular builds a partial (21/2D) Brep from scattered data. The recognition module matches this scene description with a model database and outputs recognized objects, their positions and orientations, and possibly surfaces corresponding to unknown objects. We present preliminary results in scene segmentation and recognition. Partial Brep's corresponding to different range sensors or viewpoints can be merged into a consistent, complete and irredundant 3D object or scene model. This fusion algorithm itself uses the recognition and segmentation methods.

  11. Appearance-based face recognition and light-fields.

    PubMed

    Gross, Ralph; Matthews, Iain; Baker, Simon

    2004-04-01

    Arguably the most important decision to be made when developing an object recognition algorithm is selecting the scene measurements or features on which to base the algorithm. In appearance-based object recognition, the features are chosen to be the pixel intensity values in an image of the object. These pixel intensities correspond directly to the radiance of light emitted from the object along certain rays in space. The set of all such radiance values over all possible rays is known as the plenoptic function or light-field. In this paper, we develop a theory of appearance-based object recognition from light-fields. This theory leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards. All of the pixels, whichever image they come from, are treated equally and used to estimate the (eigen) light-field of the object. The eigen light-field is then used as the set of features on which to base recognition, analogously to how the pixel intensities are used in appearance-based face and object recognition.

  12. Object classification for obstacle avoidance

    NASA Astrophysics Data System (ADS)

    Regensburger, Uwe; Graefe, Volker

    1991-03-01

    Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.

  13. Neuroprotective effects of Bacopa monnieri (Brahmi) on novel object recognition and NMDAR1 immunodensity in the prefrontal cortex, striatum and hippocampus of sub-chronic phencyclidine rat model of schizophrenia.

    PubMed

    Piyabhan, Pritsana; Wetchateng, Thanitsara

    2014-08-01

    Cognitive impairment is a major problem, which eventually develops in schizophrenia. It contributes to the patients 'functional disability and cannot be attenuated by antipsychotic drugs. Bacopa monnieri (Brahmi), a neuroprotective herbal medicine in the elderly, might be a novel neuroprotective agent for prevention of cognitive deficit in schizophrenia. To study neuroprotective effects ofBrahmi on novel object recognition task and cerebral glutamate/N-methyl-D- aspartate receptor subtype 1 (NMDAR1) immunodensity in sub-chronic phencyclidine (PCP) rat model ofschizophrenia. Rats were assigned to three groups; Group-A: Control, Group-B: PCP administration and Group- C: Brahmi + PCP. Discrimination ratio (DR) representing cognitive ability was obtainedfrom novel object recognition task. NMDAR1 immunodensity was measured in prefrontal cortex, striatum, cornu ammonis fields I (CA 1) and 2/3 (CA2/3) and dentate gyrus (DG) using immunohistochemistry. DR was significantly reduced in PCP group compared with control. This occurred alongside NMDAR1 up-regulation in CA2/3 and DG but not in prefrontal cortex, striatum or CA1. Brahmi + PCP group showed an increased DR score up to normal which occurred alongside a significantly decreased NMDARI immunodensity in CA2/3 and DG compared with PCP group. Cognitive deficit observed in rats receiving PCP was mediated by NMDAR1 up-regulation in CA2/3 and DG Interestingly, receiving Brahmi before PCP administration can restore this cognitive deficit by decreasingNMDAR1 in these brain areas. Therefore, Brahmi could be a novel neuroprotective agentfor the prevention ofcognitive deficit in schizophrenia.

  14. Learned Non-Rigid Object Motion is a View-Invariant Cue to Recognizing Novel Objects

    PubMed Central

    Chuang, Lewis L.; Vuong, Quoc C.; Bülthoff, Heinrich H.

    2012-01-01

    There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint. PMID:22661939

  15. Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad; Shirkhodaie, Amir

    2013-05-01

    Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

  16. Target recognition for ladar range image using slice image

    NASA Astrophysics Data System (ADS)

    Xia, Wenze; Han, Shaokun; Wang, Liang

    2015-12-01

    A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

  17. Role of the Anterior Cingulate Cortex in the Retrieval of Novel Object Recognition Memory after a Long Delay

    ERIC Educational Resources Information Center

    Pezze, Marie A.; Marshall, Hayley J.; Fone, Kevin C. F.; Cassaday, Helen J.

    2017-01-01

    Previous in vivo electrophysiological studies suggest that the anterior cingulate cortex (ACgx) is an important substrate of novel object recognition (NOR) memory. However, intervention studies are needed to confirm this conclusion and permanent lesion studies cannot distinguish effects on encoding and retrieval. The interval between encoding and…

  18. Assessment of Motor Function, Sensory Motor Gating and Recognition Memory in a Novel BACHD Transgenic Rat Model for Huntington Disease

    PubMed Central

    Abada, Yah-se K.; Nguyen, Huu Phuc; Schreiber, Rudy; Ellenbroek, Bart

    2013-01-01

    Rationale Huntington disease (HD) is frequently first diagnosed by the appearance of motor symptoms; the diagnosis is subsequently confirmed by the presence of expanded CAG repeats (> 35) in the HUNTINGTIN (HTT) gene. A BACHD rat model for HD carrying the human full length mutated HTT with 97 CAG-CAA repeats has been established recently. Behavioral phenotyping of BACHD rats will help to determine the validity of this model and its potential use in preclinical drug discovery studies. Objectives The present study seeks to characterize the progressive emergence of motor, sensorimotor and cognitive deficits in BACHD rats. Materials and Methods Wild type and transgenic rats were tested from 1 till 12 months of age. Motor tests were selected to measure spontaneous locomotor activity (open field) and gait coordination. Sensorimotor gating was assessed in acoustic startle response paradigms and recognition memory was evaluated in an object recognition test. Results Transgenic rats showed hyperactivity at 1 month and hypoactivity starting at 4 months of age. Motor coordination imbalance in a Rotarod test was present at 2 months and gait abnormalities were seen in a Catwalk test at 12 months. Subtle sensorimotor changes were observed, whereas object recognition was unimpaired in BACHD rats up to 12 months of age. Conclusion The current BACHD rat model recapitulates certain symptoms from HD patients, especially the marked motor deficits. A subtle neuropsychological phenotype was found and further studies are needed to fully address the sensorimotor phenotype and the potential use of BACHD rats for drug discovery purposes. PMID:23874679

  19. The effect of Wi-Fi electromagnetic waves in unimodal and multimodal object recognition tasks in male rats.

    PubMed

    Hassanshahi, Amin; Shafeie, Seyed Ali; Fatemi, Iman; Hassanshahi, Elham; Allahtavakoli, Mohammad; Shabani, Mohammad; Roohbakhsh, Ali; Shamsizadeh, Ali

    2017-06-01

    Wireless internet (Wi-Fi) electromagnetic waves (2.45 GHz) have widespread usage almost everywhere, especially in our homes. Considering the recent reports about some hazardous effects of Wi-Fi signals on the nervous system, this study aimed to investigate the effect of 2.4 GHz Wi-Fi radiation on multisensory integration in rats. This experimental study was done on 80 male Wistar rats that were allocated into exposure and sham groups. Wi-Fi exposure to 2.4 GHz microwaves [in Service Set Identifier mode (23.6 dBm and 3% for power and duty cycle, respectively)] was done for 30 days (12 h/day). Cross-modal visual-tactile object recognition (CMOR) task was performed by four variations of spontaneous object recognition (SOR) test including standard SOR, tactile SOR, visual SOR, and CMOR tests. A discrimination ratio was calculated to assess the preference of animal to the novel object. The expression levels of M1 and GAT1 mRNA in the hippocampus were assessed by quantitative real-time RT-PCR. Results demonstrated that rats in Wi-Fi exposure groups could not discriminate significantly between the novel and familiar objects in any of the standard SOR, tactile SOR, visual SOR, and CMOR tests. The expression of M1 receptors increased following Wi-Fi exposure. In conclusion, results of this study showed that chronic exposure to Wi-Fi electromagnetic waves might impair both unimodal and cross-modal encoding of information.

  20. Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

    PubMed

    Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

    2017-12-01

    The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

    PubMed

    Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

    2011-10-01

    This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

  2. Risperidone reverses the spatial object recognition impairment and hippocampal BDNF-TrkB signalling system alterations induced by acute MK-801 treatment

    PubMed Central

    Chen, Guangdong; Lin, Xiaodong; Li, Gongying; Jiang, Diego; Lib, Zhiruo; Jiang, Ronghuan; Zhuo, Chuanjun

    2017-01-01

    The aim of the present study was to investigate the effects of a commonly-used atypical antipsychotic, risperidone, on alterations in spatial learning and in the hippocampal brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signalling system caused by acute dizocilpine maleate (MK-801) treatment. In experiment 1, adult male Sprague-Dawley rats subjected to acute treatment of either low-dose MK801 (0.1 mg/kg) or normal saline (vehicle) were tested for spatial object recognition and hippocampal expression levels of BDNF, TrkB and the phophorylation of TrkB (p-TrkB). We found that compared to the vehicle, MK-801 treatment impaired spatial object recognition of animals and downregulated the expression levels of p-TrkB. In experiment 2, MK-801- or vehicle-treated animals were further injected with risperidone (0.1 mg/kg) or vehicle before behavioural testing and sacrifice. Of note, we found that risperidone successfully reversed the deleterious effects of MK-801 on spatial object recognition and upregulated the hippocampal BDNF-TrkB signalling system. Collectively, the findings suggest that cognitive deficits from acute N-methyl-D-aspartate receptor blockade may be associated with the hypofunction of hippocampal BDNF-TrkB signalling system and that risperidone was able to reverse these alterations. PMID:28451387

  3. Remembering the object you fear: brain potentials during recognition of spiders in spider-fearful individuals.

    PubMed

    Michalowski, Jaroslaw M; Weymar, Mathias; Hamm, Alfons O

    2014-01-01

    In the present study we investigated long-term memory for unpleasant, neutral and spider pictures in 15 spider-fearful and 15 non-fearful control individuals using behavioral and electrophysiological measures. During the initial (incidental) encoding, pictures were passively viewed in three separate blocks and were subsequently rated for valence and arousal. A recognition memory task was performed one week later in which old and new unpleasant, neutral and spider pictures were presented. Replicating previous results, we found enhanced memory performance and higher confidence ratings for unpleasant when compared to neutral materials in both animal fearful individuals and controls. When compared to controls high animal fearful individuals also showed a tendency towards better memory accuracy and significantly higher confidence during recognition of spider pictures, suggesting that memory of objects prompting specific fear is also facilitated in fearful individuals. In line, spider-fearful but not control participants responded with larger ERP positivity for correctly recognized old when compared to correctly rejected new spider pictures, thus showing the same effects in the neural signature of emotional memory for feared objects that were already discovered for other emotional materials. The increased fear memory for phobic materials observed in the present study in spider-fearful individuals might result in an enhanced fear response and reinforce negative beliefs aggravating anxiety symptomatology and hindering recovery.

  4. Spatial-frequency cutoff requirements for pattern recognition in central and peripheral vision

    PubMed Central

    Kwon, MiYoung; Legge, Gordon E.

    2011-01-01

    It is well known that object recognition requires spatial frequencies exceeding some critical cutoff value. People with central scotomas who rely on peripheral vision have substantial difficulty with reading and face recognition. Deficiencies of pattern recognition in peripheral vision, might result in higher cutoff requirements, and may contribute to the functional problems of people with central-field loss. Here we asked about differences in spatial-cutoff requirements in central and peripheral vision for letter and face recognition. The stimuli were the 26 letters of the English alphabet and 26 celebrity faces. Each image was blurred using a low-pass filter in the spatial frequency domain. Critical cutoffs (defined as the minimum low-pass filter cutoff yielding 80% accuracy) were obtained by measuring recognition accuracy as a function of cutoff (in cycles per object). Our data showed that critical cutoffs increased from central to peripheral vision by 20% for letter recognition and by 50% for face recognition. We asked whether these differences could be accounted for by central/peripheral differences in the contrast sensitivity function (CSF). We addressed this question by implementing an ideal-observer model which incorporates empirical CSF measurements and tested the model on letter and face recognition. The success of the model indicates that central/peripheral differences in the cutoff requirements for letter and face recognition can be accounted for by the information content of the stimulus limited by the shape of the human CSF, combined with a source of internal noise and followed by an optimal decision rule. PMID:21854800

  5. An optical processor for object recognition and tracking

    NASA Technical Reports Server (NTRS)

    Sloan, J.; Udomkesmalee, S.

    1987-01-01

    The design and development of a miniaturized optical processor that performs real time image correlation are described. The optical correlator utilizes the Vander Lugt matched spatial filter technique. The correlation output, a focused beam of light, is imaged onto a CMOS photodetector array. In addition to performing target recognition, the device also tracks the target. The hardware, composed of optical and electro-optical components, occupies only 590 cu cm of volume. A complete correlator system would also include an input imaging lens. This optical processing system is compact, rugged, requires only 3.5 watts of operating power, and weighs less than 3 kg. It represents a major achievement in miniaturizing optical processors. When considered as a special-purpose processing unit, it is an attractive alternative to conventional digital image recognition processing. It is conceivable that the combined technology of both optical and ditital processing could result in a very advanced robot vision system.

  6. Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

    NASA Astrophysics Data System (ADS)

    Fiorini, Rodolfo A.; Dacquino, Gianfranco

    2005-03-01

    GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

  7. Face Processing: Models For Recognition

    NASA Astrophysics Data System (ADS)

    Turk, Matthew A.; Pentland, Alexander P.

    1990-03-01

    The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

  8. Young Children's Self-Generated Object Views and Object Recognition

    ERIC Educational Resources Information Center

    James, Karin H.; Jones, Susan S.; Smith, Linda B.; Swain, Shelley N.

    2014-01-01

    Two important and related developments in children between 18 and 24 months of age are the rapid expansion of object name vocabularies and the emergence of an ability to recognize objects from sparse representations of their geometric shapes. In the same period, children also begin to show a preference for planar views (i.e., views of objects held…

  9. Evidence for the activation of sensorimotor information during visual word recognition: the body-object interaction effect.

    PubMed

    Siakaluk, Paul D; Pexman, Penny M; Aguilera, Laura; Owen, William J; Sears, Christopher R

    2008-01-01

    We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a word's referent. A set of high BOI words (e.g., mask) and a set of low BOI words (e.g., ship) were created, matched on imageability and concreteness. Facilitatory BOI effects were observed in lexical decision and phonological lexical decision tasks: responses were faster for high BOI words than for low BOI words. We discuss how our findings may be accounted for by (a) semantic feedback within the visual word recognition system, and (b) an embodied view of cognition (e.g., Barsalou's perceptual symbol systems theory), which proposes that semantic knowledge is grounded in sensorimotor interactions with the environment.

  10. Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

    NASA Technical Reports Server (NTRS)

    Juday, Richard D. (Editor)

    1988-01-01

    The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

  11. The Hierarchical Brain Network for Face Recognition

    PubMed Central

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282

  12. The hierarchical brain network for face recognition.

    PubMed

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  13. The Effect of Inversion on 3- to 5-Year-Olds' Recognition of Face and Nonface Visual Objects

    ERIC Educational Resources Information Center

    Picozzi, Marta; Cassia, Viola Macchi; Turati, Chiara; Vescovo, Elena

    2009-01-01

    This study compared the effect of stimulus inversion on 3- to 5-year-olds' recognition of faces and two nonface object categories matched with faces for a number of attributes: shoes (Experiment 1) and frontal images of cars (Experiments 2 and 3). The inversion effect was present for faces but not shoes at 3 years of age (Experiment 1). Analogous…

  14. A Longitudinal Study of Cognitive Representation in Symbolic Play, Self-recognition, and Object Permanence during the Second Year.

    ERIC Educational Resources Information Center

    Chapman, Michael

    1987-01-01

    Explores development of cognitive representation in 20 infants 12 to 24 months of age with regard to (l) their understanding of agency in symbolic play (agent use), (2) recognition of their own mirror image, and (3) object permanence. Results were generally consistent with developmental sequences predicted by Fischer's Skill Theory for agent use…

  15. Estradiol-Induced Object Recognition Memory Consolidation Is Dependent on Activation of mTOR Signaling in the Dorsal Hippocampus

    ERIC Educational Resources Information Center

    Fortress, Ashley M.; Fan, Lu; Orr, Patrick T.; Zhao, Zaorui; Frick, Karyn M.

    2013-01-01

    The mammalian target of rapamycin (mTOR) signaling pathway is an important regulator of protein synthesis and is essential for various forms of hippocampal memory. Here, we asked whether the enhancement of object recognition memory consolidation produced by dorsal hippocampal infusion of 17[Beta]-estradiol (E[subscript 2]) is dependent on mTOR…

  16. Effect of 1.8 GHz radiofrequency electromagnetic radiation on novel object associative recognition memory in mice

    PubMed Central

    Wang, Kai; Lu, Jun-Mei; Xing, Zhen-He; Zhao, Qian-Ru; Hu, Lin-Qi; Xue, Lei; Zhang, Jie; Mei, Yan-Ai

    2017-01-01

    Mounting evidence suggests that exposure to radiofrequency electromagnetic radiation (RF-EMR) can influence learning and memory in rodents. In this study, we examined the effects of single exposure to 1.8 GHz RF-EMR for 30 min on subsequent recognition memory in mice, using the novel object recognition task (NORT). RF-EMR exposure at an intensity of >2.2 W/kg specific absorption rate (SAR) power density induced a significant density-dependent increase in NORT index with no corresponding changes in spontaneous locomotor activity. RF-EMR exposure increased dendritic-spine density and length in hippocampal and prefrontal cortical neurons, as shown by Golgi staining. Whole-cell recordings in acute hippocampal and medial prefrontal cortical slices showed that RF-EMR exposure significantly altered the resting membrane potential and action potential frequency, and reduced the action potential half-width, threshold, and onset delay in pyramidal neurons. These results demonstrate that exposure to 1.8 GHz RF-EMR for 30 min can significantly increase recognition memory in mice, and can change dendritic-spine morphology and neuronal excitability in the hippocampus and prefrontal cortex. The SAR in this study (3.3 W/kg) was outside the range encountered in normal daily life, and its relevance as a potential therapeutic approach for disorders associated with recognition memory deficits remains to be clarified. PMID:28303965

  17. Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

    PubMed

    Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

    2014-03-01

    Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

  18. A Retrieval Model for Both Recognition and Recall.

    ERIC Educational Resources Information Center

    Gillund, Gary; Shiffrin, Richard M.

    1984-01-01

    The Search of Associative Memory (SAM) model for recall is extended by assuming that a familiarity process is used for recognition. The model, formalized in a computer simulation program, correctly predicts a number of findings in the literature as well as results from an experiment on the word-frequency effect. (Author/BW)

  19. Modeling Confidence and Response Time in Recognition Memory

    ERIC Educational Resources Information Center

    Ratcliff, Roger; Starns, Jeffrey J.

    2009-01-01

    A new model for confidence judgments in recognition memory is presented. In the model, the match between a single test item and memory produces a distribution of evidence, with better matches corresponding to distributions with higher means. On this match dimension, confidence criteria are placed, and the areas between the criteria under the…

  20. The Vasopressin 1b Receptor Antagonist A-988315 Blocks Stress Effects on the Retrieval of Object-Recognition Memory

    PubMed Central

    Barsegyan, Areg; Atsak, Piray; Hornberger, Wilfried B; Jacobson, Peer B; van Gaalen, Marcel M; Roozendaal, Benno

    2015-01-01

    Stress-induced activation of the hypothalamo–pituitary–adrenocortical (HPA) axis and high circulating glucocorticoid levels are well known to impair the retrieval of memory. Vasopressin can activate the HPA axis by stimulating vasopressin 1b (V1b) receptors located on the pituitary. In the present study, we investigated the effect of A-988315, a selective and highly potent non-peptidergic V1b-receptor antagonist with good pharmacokinetic properties, in blocking stress effects on HPA-axis activity and memory retrieval. To study cognitive performance, male Sprague-Dawley rats were trained on an object-discrimination task during which they could freely explore two identical objects. Memory for the objects and their location was tested 24 h later. A-988315 (20 or 60 mg/kg) or water was administered orally 90 min before retention testing, followed 60 min later by stress of footshock exposure. A-988315 dose-dependently dampened stress-induced increases in corticosterone plasma levels, but did not significantly alter HPA-axis activity of non-stressed control rats. Most importantly, A-988315 administration prevented stress-induced impairment of memory retrieval on both the object-recognition and the object-location tasks. A-988315 did not alter the retention of non-stressed rats and did not influence the total time spent exploring the objects or experimental context in either stressed or non-stressed rats. Thus, these findings indicate that direct antagonism of V1b receptors is an effective treatment to block stress-induced activation of the HPA axis and the consequent impairment of retrieval of different aspects of recognition memory. PMID:25669604

  1. Behavior analysis of video object in complicated background

    NASA Astrophysics Data System (ADS)

    Zhao, Wenting; Wang, Shigang; Liang, Chao; Wu, Wei; Lu, Yang

    2016-10-01

    This paper aims to achieve robust behavior recognition of video object in complicated background. Features of the video object are described and modeled according to the depth information of three-dimensional video. Multi-dimensional eigen vector are constructed and used to process high-dimensional data. Stable object tracing in complex scenes can be achieved with multi-feature based behavior analysis, so as to obtain the motion trail. Subsequently, effective behavior recognition of video object is obtained according to the decision criteria. What's more, the real-time of algorithms and accuracy of analysis are both improved greatly. The theory and method on the behavior analysis of video object in reality scenes put forward by this project have broad application prospect and important practical significance in the security, terrorism, military and many other fields.

  2. The short and long term effects of docetaxel chemotherapy on rodent object recognition and spatial reference memory.

    PubMed

    Fardell, Joanna E; Vardy, Janette; Johnston, Ian N

    2013-10-17

    Previous animal studies have examined the potential for cytostatic drugs to induce learning and memory deficits in laboratory animals but, to date, there is no pre-clinical evidence that taxanes have the potential to cause cognitive impairment. Therefore our aim was to explore the short- and long-term cognitive effects of different dosing schedules of the taxane docetaxel (DTX) on laboratory rodents. Healthy male hooded Wistar rats were treated with DTX (6 mg/kg, 10mg/kg) or physiological saline (control), once a week for 3 weeks (Experiment 1) or once only (10mg/kg; Experiment 2). Cognitive function was assessed using the novel object recognition (NOR) task and spatial water maze (WM) task 1 to 3 weeks after treatment and again 4 months after treatment. Shortly after DTX treatment, rats perform poorly on NOR regardless of treatment regimen. Treatment with a single injection of 10mg/kg DTX does not appear to induce sustained deficits in object recognition or peripheral neuropathy. Overall these findings show that treatment with the taxane DTX in the absence of cancer and other anti-cancer treatments causes cognitive impairment in healthy rodents. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. The recognition of graphical patterns invariant to geometrical transformation of the models

    NASA Astrophysics Data System (ADS)

    Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

    2010-11-01

    In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

  4. Effect of +-methamphetamine on path integration learning, novel object recognition, and neurotoxicity in rats.

    PubMed

    Herring, Nicole R; Schaefer, Tori L; Gudelsky, Gary A; Vorhees, Charles V; Williams, Michael T

    2008-09-01

    Methamphetamine (MA) has been implicated in cognitive deficits in humans after chronic use. Animal models of neurotoxic MA exposure reveal persistent damage to monoaminergic systems but few associated cognitive effects. Since questions have been raised about the typical neurotoxic dosing regimen used in animals and whether it adequately models human cumulative drug exposure, these experiments examined two different dosing regimens. Rats were treated with one of the two regimens: one based on the typical neurotoxic regimen (4 x 10 mg/kg every 2 h) and one based on pharmacokinetic modeling (Cho AK, Melega WP, Kuczenski R, Segal DS Synapse 39:161-166, 2001) designed to better represent accumulating plasma concentrations of MA as seen in human users (24 x 1.67 mg/kg once every 15 min) matched for total daily dose. In two separate experiments, dosing regimens were compared for their effects on markers of neurotoxicity or on behavior. On markers of neurotoxicity, MA showed decreased dopamine (DA) and 5-HT, increased glial fibrillary acidic protein, and increased corticosterone levels regardless of dosing regimen 3 days post-treatment. Behaviorally, MA-treated groups, regardless of dosing regimen, showed hypoactivity, increased initial hyperactivity to a subsequent MA challenge, impaired novel object recognition, impaired learning in a multiple T water maze test of path integration, and no differences on spatial navigation or reference memory in the Morris water maze. After behavioral testing, reductions of DA and 5-HT remained. MA treatment induces an effect on path integration learning not previously reported. Dosing regimen had no differential effects on behavior or neurotoxicity.

  5. Dissociating electrophysiological correlates of subjective, objective, and correct memory in investigating the emotion-induced recognition bias.

    PubMed

    Windmann, Sabine; Hill, Holger

    2014-10-01

    Performance on tasks requiring discrimination of at least two stimuli can be viewed either from an objective perspective (referring to actual stimulus differences), or from a subjective perspective (corresponding to participant's responses). Using event-related potentials recorded during an old/new recognition memory test involving emotionally laden and neutral words studied either blockwise or randomly intermixed, we show here how the objective perspective (old versus new items) yields late effects of blockwise emotional item presentation at parietal sites that the subjective perspective fails to find, whereas the subjective perspective ("old" versus "new" responses) is more sensitive to early effects of emotion at anterior sites than the objective perspective. Our results demonstrate the potential advantage of dissociating the subjective and the objective perspective onto task performance (in addition to analyzing trials with correct responses), especially for investigations of illusions and information processing biases, in behavioral and cognitive neuroscience studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

    PubMed

    Bennetts, Rachel J; Mole, Joseph; Bate, Sarah

    2017-09-01

    Face recognition abilities vary widely. While face recognition deficits have been reported in children, it is unclear whether superior face recognition skills can be encountered during development. This paper presents O.B., a 14-year-old female with extraordinary face recognition skills: a "super-recognizer" (SR). O.B. demonstrated exceptional face-processing skills across multiple tasks, with a level of performance that is comparable to adult SRs. Her superior abilities appear to be specific to face identity: She showed an exaggerated face inversion effect and her superior abilities did not extend to object processing or non-identity aspects of face recognition. Finally, an eye-movement task demonstrated that O.B. spent more time than controls examining the nose - a pattern previously reported in adult SRs. O.B. is therefore particularly skilled at extracting and using identity-specific facial cues, indicating that face and object recognition are dissociable during development, and that super recognition can be detected in adolescence.

  7. Bayesian Action–Perception Computational Model: Interaction of Production and Recognition of Cursive Letters

    PubMed Central

    Gilet, Estelle; Diard, Julien; Bessière, Pierre

    2011-01-01

    In this paper, we study the collaboration of perception and action representations involved in cursive letter recognition and production. We propose a mathematical formulation for the whole perception–action loop, based on probabilistic modeling and Bayesian inference, which we call the Bayesian Action–Perception (BAP) model. Being a model of both perception and action processes, the purpose of this model is to study the interaction of these processes. More precisely, the model includes a feedback loop from motor production, which implements an internal simulation of movement. Motor knowledge can therefore be involved during perception tasks. In this paper, we formally define the BAP model and show how it solves the following six varied cognitive tasks using Bayesian inference: i) letter recognition (purely sensory), ii) writer recognition, iii) letter production (with different effectors), iv) copying of trajectories, v) copying of letters, and vi) letter recognition (with internal simulation of movements). We present computer simulations of each of these cognitive tasks, and discuss experimental predictions and theoretical developments. PMID:21674043

  8. Three Dimensional Object Recognition Using a Complex Autoregressive Model

    DTIC Science & Technology

    1993-12-01

    3.4.2 Template Matching Algorithm ...................... 3-16 3.4.3 K-Nearest-Neighbor ( KNN ) Techniques ................. 3-25 3.4.4 Hidden Markov Model...Neighbor ( KNN ) Test Results ...................... 4-13 4.2.1 Single-Look 1-NN Testing .......................... 4-14 4.2.2 Multiple-Look 1-NN Testing...4-15 4.2.3 Discussion of KNN Test Results ...................... 4-15 4.3 Hidden Markov Model (HMM) Test Results

  9. A self-organized learning strategy for object recognition by an embedded line of attraction

    NASA Astrophysics Data System (ADS)

    Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

    2012-04-01

    on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

  10. Self-Recognition in Autistic Children.

    ERIC Educational Resources Information Center

    Dawson, Geraldine; McKissick, Fawn Celeste

    1984-01-01

    Fifteen autistic children (four to six years old) were assessed for visual self-recognition ability, as well as for object permanence and gestural imitation. It was found that 13 of 15 autistic children showed evidence of self-recognition. Consistent relationships were suggested between self-cognition and object permanence but not between…

  11. Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making.

    PubMed

    Osth, Adam F; Jansson, Anna; Dennis, Simon; Heathcote, Andrew

    2018-08-01

    A robust finding in recognition memory is that performance declines monotonically across test trials. Despite the prevalence of this decline, there is a lack of consensus on the mechanism responsible. Three hypotheses have been put forward: (1) interference is caused by learning of test items (2) the test items cause a shift in the context representation used to cue memory and (3) participants change their speed-accuracy thresholds through the course of testing. We implemented all three possibilities in a combined model of recognition memory and decision making, which inherits the memory retrieval elements of the Osth and Dennis (2015) model and uses the diffusion decision model (DDM: Ratcliff, 1978) to generate choice and response times. We applied the model to four datasets that represent three challenges, the findings that: (1) the number of test items plays a larger role in determining performance than the number of studied items, (2) performance decreases less for strong items than weak items in pure lists but not in mixed lists, and (3) lexical decision trials interspersed between recognition test trials do not increase the rate at which performance declines. Analysis of the model's parameter estimates suggests that item interference plays a weak role in explaining the effects of recognition testing, while context drift plays a very large role. These results are consistent with prior work showing a weak role for item noise in recognition memory and that retrieval is a strong cause of context change in episodic memory. Copyright © 2018 Elsevier Inc. All rights reserved.

  12. Computational modeling of the neural representation of object shape in the primate ventral visual system

    PubMed Central

    Eguchi, Akihiro; Mender, Bedeho M. W.; Evans, Benjamin D.; Humphreys, Glyn W.; Stringer, Simon M.

    2015-01-01

    Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visual objects. In this paper, we investigate through computer simulation how these cell firing properties may develop through unsupervised visually-guided learning. Individual neurons in the model are shown to exploit statistical regularity and temporal continuity of the visual inputs during training to learn firing properties that are similar to neurons in V4 and TEO. Neurons in V4 encode the conformation of boundary contour elements at a particular position within an object regardless of the location of the object on the retina, while neurons in TEO integrate information from multiple boundary contour elements. This representation goes beyond mere object recognition, in which neurons simply respond to the presence of a whole object, but provides an essential foundation from which the brain is subsequently able to recognize the whole object. PMID:26300766

  13. Behavioral methods for the study of the Ras-ERK pathway in memory formation and consolidation: passive avoidance and novel object recognition tests.

    PubMed

    d'Isa, Raffaele; Brambilla, Riccardo; Fasano, Stefania

    2014-01-01

    Memory is a high-level brain function that enables organisms to adapt their behavioral responses to the environment, hence increasing their probability of survival. The Ras-ERK pathway is a key molecular intracellular signalling cascade for memory consolidation. In this chapter we will describe two main one-trial behavioral tests commonly used in the field of memory research in order to assess the role of Ras-ERK signalling in long-term memory: passive avoidance and object recognition. Passive avoidance (PA) is a fear-motivated instrumental learning task, designed by Jarvik and Essman in 1960, in which animals learn to refrain from emitting a behavioral response that has previously been associated with a punishment. We will describe here the detailed protocol and show some examples of how PA can reveal impairments or enhancements in memory consolidation following loss or gain of function genetic manipulations of the Ras-ERK pathway. The phenotypes of global mutants as Ras-GRF1 KO, GENA53, and ERK1 KO mice, as well as of conditional region-specific mutants (striatal K-CREB mice), will be illustrated as examples. Novel object recognition (NOR), developed by Ennaceur and Delacour in 1988, is instead a more recent and highly ecological test, which relies on the natural tendency of rodents to spontaneously approach and explore novel objects, representing hence a useful non-stressful tool for the study of memory in animals without the employment of punishments or starvation/water restriction regimens. Careful indications will be given on how to select the positions for the novel object, in order to counterbalance for individual side preferences among mice during the training. Finally, the methods for calculating two learning indexes will be described. In addition to the classical discrimination index (DI) that measures the ability of an animal to discriminate between two different objects which are presented at the same time, we will describe the formula of a new index

  14. Role of fusiform and anterior temporal cortical areas in facial recognition.

    PubMed

    Nasr, Shahin; Tootell, Roger B H

    2012-11-15

    Recent fMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus ('AT'; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Role of Fusiform and Anterior Temporal Cortical Areas in Facial Recognition

    PubMed Central

    Nasr, Shahin; Tootell, Roger BH

    2012-01-01

    Recent FMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus (‘AT’; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. PMID:23034518

  16. Genetic specificity of face recognition.

    PubMed

    Shakeshaft, Nicholas G; Plomin, Robert

    2015-10-13

    Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

  17. Products recognition on shop-racks from local scale-invariant features

    NASA Astrophysics Data System (ADS)

    Zawistowski, Jacek; Kurzejamski, Grzegorz; Garbat, Piotr; Naruniec, Jacek

    2016-04-01

    This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.

  18. Dopamine receptor activity participates in hippocampal synaptic plasticity associated with novel object recognition.

    PubMed

    Yang, Kechun; Broussard, John I; Levine, Amber T; Jenson, Daniel; Arenkiel, Benjamin R; Dani, John A

    2017-01-01

    Physiological and behavioral evidence supports that dopamine (DA) receptor signaling influences hippocampal function. While several recent studies examined how DA influences CA1 plasticity and learning, there are fewer studies investigating the influence of DA signaling to the dentate gyrus. The dentate gyrus receives convergent cortical input through the perforant path fiber tracts and has been conceptualized to detect novelty in spatial memory tasks. To test whether DA-receptor activity influences novelty-detection, we used a novel object recognition (NOR) task where mice remember previously presented objects as an indication of learning. Although DA innervation arises from other sources and the main DA signaling may be from those sources, our molecular approaches verified that midbrain dopaminergic fibers also sparsely innervate the dentate gyrus. During the NOR task, wild-type mice spent significantly more time investigating novel objects rather than previously observed objects. Dentate granule cells in slices cut from those mice showed an increased AMPA/NMDA-receptor current ratio indicative of potentiated synaptic transmission. Post-training injection of a D1-like receptor antagonist not only effectively blocked the preference for the novel objects, but also prevented the increased AMPA/NMDA ratio. Consistent with that finding, neither NOR learning nor the increase in the AMPA/NMDA ratio were observed in DA-receptor KO mice under the same experimental conditions. The results indicate that DA-receptor signaling contributes to the successful completion of the NOR task and to the associated synaptic plasticity of the dentate gyrus that likely contributes to the learning. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  19. Self-organizing neural network models for visual pattern recognition.

    PubMed

    Fukushima, K

    1987-01-01

    Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

  20. Beyond perceptual expertise: revisiting the neural substrates of expert object recognition

    PubMed Central

    Harel, Assaf; Kravitz, Dwight; Baker, Chris I.

    2013-01-01

    Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex. PMID:24409134