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Sample records for 3d object recognition

  1. New method of 3-D object recognition

    NASA Astrophysics Data System (ADS)

    He, An-Zhi; Li, Qun Z.; Miao, Peng C.

    1991-12-01

    In this paper, a new method of 3-D object recognition using optical techniques and a computer is presented. We perform 3-D object recognition using moire contour to obtain the object's 3- D coordinates, projecting drawings of the object in three coordinate planes to describe it and using a method of inquiring library of judgement to match objects. The recognition of a simple geometrical entity is simulated by computer and studied experimentally. The recognition of an object which is composed of a few simple geometrical entities is discussed.

  2. 3-D object recognition using 2-D views.

    PubMed

    Li, Wenjing; Bebis, George; Bourbakis, Nikolaos G

    2008-11-01

    We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize instances of specific objects (i.e., model-based) in a scene. This is in contrast to category-based object recognition methods where the goal is to search for instances of objects that belong to a certain visual category (e.g., faces or cars). The key contribution of our work is improving 3-D object recognition by integrating Algebraic Functions of Views (AFoVs), a powerful framework for predicting the geometric appearance of an object due to viewpoint changes, with indexing and learning. During training, we compute the space of views that groups of object features can produce under the assumption of 3-D linear transformations, by combining a small number of reference views that contain the object features using AFoVs. Unrealistic views (e.g., due to the assumption of 3-D linear transformations) are eliminated by imposing a pair of rigidity constraints based on knowledge of the transformation between the reference views of the object. To represent the space of views that an object can produce compactly while allowing efficient hypothesis generation during recognition, we propose combining indexing with learning in two stages. In the first stage, we sample the space of views of an object sparsely and represent information about the samples using indexing. In the second stage, we build probabilistic models of shape appearance by sampling the space of views of the object densely and learning the manifold formed by the samples. Learning employs the Expectation-Maximization (EM) algorithm and takes place in a "universal," lower-dimensional, space computed through Random Projection (RP). During recognition, we extract groups of point features from the scene and we use indexing to retrieve the most feasible model groups that might have produced them (i.e., hypothesis generation). The likelihood

  3. A Primitive-Based 3D Object Recognition System

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.

    1988-08-01

    A knowledge-based 3D object recognition system has been developed. The system uses the hierarchical structural, geometrical and relational knowledge in matching the 3D object models to the image data through pre-defined primitives. The primitives, we have selected, to begin with, are 3D boxes, cylinders, and spheres. These primitives as viewed from different angles covering complete 3D rotation range are stored in a "Primitive-Viewing Knowledge-Base" in form of hierarchical structural and relational graphs. The knowledge-based system then hypothesizes about the viewing angle and decomposes the segmented image data into valid primitives. A rough 3D structural and relational description is made on the basis of recognized 3D primitives. This description is now used in the detailed high-level frame-based structural and relational matching. The system has several expert and knowledge-based systems working in both stand-alone and cooperative modes to provide multi-level processing. This multi-level processing utilizes both bottom-up (data-driven) and top-down (model-driven) approaches in order to acquire sufficient knowledge to accept or reject any hypothesis for matching or recognizing the objects in the given image.

  4. Objective 3D face recognition: Evolution, approaches and challenges.

    PubMed

    Smeets, Dirk; Claes, Peter; Vandermeulen, Dirk; Clement, John Gerald

    2010-09-10

    Face recognition is a natural human ability and a widely accepted identification and authentication method. In modern legal settings, a lot of credence is placed on identifications made by eyewitnesses. Consequently these are based on human perception which is often flawed and can lead to situations where identity is disputed. Therefore, there is a clear need to secure identifications in an objective way based on anthropometric measures. Anthropometry has existed for many years and has evolved with each advent of new technology and computing power. As a result of this, face recognition methodology has shifted from a purely 2D image-based approach to the use of 3D facial shape. However, one of the main challenges still remaining is the non-rigid structure of the face, which can change permanently over varying time-scales and briefly with facial expressions. The majority of face recognition methods have been developed by scientists with a very technical background such as biometry, pattern recognition and computer vision. This article strives to bridge the gap between these communities and the forensic science end-users. A concise review of face recognition using 3D shape is given. Methods using 3D shape applied to data embodying facial expressions are tabulated for reference. From this list a categorization of different strategies to deal with expressions is presented. The underlying concepts and practical issues relating to the application of each strategy are given, without going into technical details. The discussion clearly articulates the justification to establish archival, reference databases to compare and evaluate different strategies. PMID:20395086

  5. 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

  6. 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.

  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. Combining depth and color data for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Joergensen, Thomas M.; Linneberg, Christian; Andersen, Allan W.

    1997-09-01

    This paper describes the shape recognition system that has been developed within the ESPRIT project 9052 ADAS on automatic disassembly of TV-sets using a robot cell. Depth data from a chirped laser radar are fused with color data from a video camera. The sensor data is pre-processed in several ways and the obtained representation is used to train a RAM neural network (memory based reasoning approach) to detect different components within TV-sets. The shape recognizing architecture has been implemented and tested in a demonstration setup.

  9. 3D video analysis of the novel object recognition test in rats.

    PubMed

    Matsumoto, Jumpei; Uehara, Takashi; Urakawa, Susumu; Takamura, Yusaku; Sumiyoshi, Tomiki; Suzuki, Michio; Ono, Taketoshi; Nishijo, Hisao

    2014-10-01

    The novel object recognition (NOR) test has been widely used to test memory function. We developed a 3D computerized video analysis system that estimates nose contact with an object in Long Evans rats to analyze object exploration during NOR tests. The results indicate that the 3D system reproducibly and accurately scores the NOR test. Furthermore, the 3D system captures a 3D trajectory of the nose during object exploration, enabling detailed analyses of spatiotemporal patterns of object exploration. The 3D trajectory analysis revealed a specific pattern of object exploration in the sample phase of the NOR test: normal rats first explored the lower parts of objects and then gradually explored the upper parts. A systematic injection of MK-801 suppressed changes in these exploration patterns. The results, along with those of previous studies, suggest that the changes in the exploration patterns reflect neophobia to a novel object and/or changes from spatial learning to object learning. These results demonstrate that the 3D tracking system is useful not only for detailed scoring of animal behaviors but also for investigation of characteristic spatiotemporal patterns of object exploration. The system has the potential to facilitate future investigation of neural mechanisms underlying object exploration that result from dynamic and complex brain activity. PMID:24991752

  10. A Global Hypothesis Verification Framework for 3D Object Recognition in Clutter.

    PubMed

    Aldoma, Aitor; Tombari, Federico; Stefano, Luigi Di; Vincze, Markus

    2016-07-01

    Pipelines to recognize 3D objects despite clutter and occlusions usually end up with a final verification stage whereby recognition hypotheses are validated or dismissed based on how well they explain sensor measurements. Unlike previous work, we propose a Global Hypothesis Verification (GHV) approach which regards all hypotheses jointly so as to account for mutual interactions. GHV provides a principled framework to tackle the complexity of our visual world by leveraging on a plurality of recognition paradigms and cues. Accordingly, we present a 3D object recognition pipeline deploying both global and local 3D features as well as shape and color. Thereby, and facilitated by the robustness of the verification process, diverse object hypotheses can be gathered and weak hypotheses need not be suppressed too early to trade sensitivity for specificity. Experiments demonstrate the effectiveness of our proposal, which significantly improves over the state-of-art and attains ideal performance (no false negatives, no false positives) on three out of the six most relevant and challenging benchmark datasets. PMID:26485476

  11. Intraclass retrieval of nonrigid 3D objects: application to face recognition.

    PubMed

    Passalis, Georgios; Kakadiaris, Ioannis A; Theoharis, Theoharis

    2007-02-01

    As the size of the available collections of 3D objects grows, database transactions become essential for their management with the key operation being retrieval (query). Large collections are also precategorized into classes so that a single class contains objects of the same type (e.g., human faces, cars, four-legged animals). It is shown that general object retrieval methods are inadequate for intraclass retrieval tasks. We advocate that such intraclass problems require a specialized method that can exploit the basic class characteristics in order to achieve higher accuracy. A novel 3D object retrieval method is presented which uses a parameterized annotated model of the shape of the class objects, incorporating its main characteristics. The annotated subdivision-based model is fitted onto objects of the class using a deformable model framework, converted to a geometry image and transformed into the wavelet domain. Object retrieval takes place in the wavelet domain. The method does not require user interaction, achieves high accuracy, is efficient for use with large databases, and is suitable for nonrigid object classes. We apply our method to the face recognition domain, one of the most challenging intraclass retrieval tasks. We used the Face Recognition Grand Challenge v2 database, yielding an average verification rate of 95.2 percent at 10-3 false accept rate. The latest results of our work can be found at http://www.cbl.uh.edu/UR8D/. PMID:17170476

  12. Neural network techniques for invariant recognition and motion tracking of 3-D objects

    SciTech Connect

    Hwang, J.N.; Tseng, Y.H.

    1995-12-31

    Invariant recognition and motion tracking of 3-D objects under partial object viewing are difficult tasks. In this paper, we introduce a new neural network solution that is robust to noise corruption and partial viewing of objects. This method directly utilizes the acquired range data and requires no feature extraction. In the proposed approach, the object is first parametrically represented by a continuous distance transformation neural network (CDTNN) which is trained by the surface points of the exemplar object. When later presented with the surface points of an unknown object, this parametric representation allows the mismatch information to back-propagate through the CDTNN to gradually determine the best similarity transformation (translation and rotation) of the unknown object. The mismatch can be directly measured in the reconstructed representation domain between the model and the unknown object.

  13. A 3D approach for object recognition in illuminated scenes with adaptive correlation filters

    NASA Astrophysics Data System (ADS)

    Picos, Kenia; Díaz-Ramírez, Víctor H.

    2015-09-01

    In this paper we solve the problem of pose recognition of a 3D object in non-uniformly illuminated and noisy scenes. The recognition system employs a bank of space-variant correlation filters constructed with an adaptive approach based on local statistical parameters of the input scene. The position and orientation of the target are estimated with the help of the filter bank. For an observed input frame, the algorithm computes the correlation process between the observed image and the bank of filters using a combination of data and task parallelism by taking advantage of a graphics processing unit (GPU) architecture. The pose of the target is estimated by finding the template that better matches the current view of target within the scene. The performance of the proposed system is evaluated in terms of recognition accuracy, location and orientation errors, and computational performance.

  14. 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.

  15. Hybrid system of optics and computer for 3-D object recognition

    NASA Astrophysics Data System (ADS)

    Li, Qun Z.; Miao, Peng C.; He, Anzhi

    1992-03-01

    In this paper, a hybrid system of optics and computer for 3D object recognition is presented. The system consists of a Twyman-Green interferometer, a He-Ne laser, a computer, a TV camera, and an image processor. The structured light produced by a Twyman-Green interferometer is split in and illuminates objects in two directions at the same time. Moire contour is formed on the surface of object. In order to delete unwanted patterns in moire contour, we don't utilize the moire contour on the surface of object. We place a TV camera in the middle of the angle between two illuminating directions and take two groups of deformed fringes on the surface of objects. Two groups of deformed fringes are processed using the digital image processing system controlled and operated by XOR logic in the computer, moire fringes are then extracted from the complicated environment. 3D coordinates of points of the object are obtained after moire fringe is followed, and points belonging to the same fringe are given the same altitude. The object is described by its projected drawings in three coordinate planes. The projected drawings in three coordinate planes of the known objects are stored in the library of judgment. The object can be recognized by inquiring the library of judgment.

  16. An optimal sensing strategy for recognition and localization of 3-D natural quadric objects

    NASA Technical Reports Server (NTRS)

    Lee, Sukhan; Hahn, Hernsoo

    1991-01-01

    An optimal sensing strategy for an optical proximity sensor system engaged in the recognition and localization of 3-D natural quadric objects is presented. The optimal sensing strategy consists of the selection of an optimal beam orientation and the determination of an optimal probing plane that compose an optimal data collection operation known as an optimal probing. The decision of an optimal probing is based on the measure of discrimination power of a cluster of surfaces on a multiple interpretation image (MII), where the measure of discrimination power is defined in terms of a utility function computing the expected number of interpretations that can be pruned out by a probing. An object representation suitable for active sensing based on a surface description vector (SDV) distribution graph and hierarchical tables is presented. Experimental results are shown.

  17. 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.

  18. 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. PMID:26886006

  19. 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

  20. Automatic 3D object recognition and reconstruction based on neuro-fuzzy modelling

    NASA Astrophysics Data System (ADS)

    Samadzadegan, Farhad; Azizi, Ali; Hahn, Michael; Lucas, Curo

    Three-dimensional object recognition and reconstruction (ORR) is a research area of major interest in computer vision and photogrammetry. Virtual cities, for example, is one of the exciting application fields of ORR which became very popular during the last decade. Natural and man-made objects of cities such as trees and buildings are complex structures and automatic recognition and reconstruction of these objects from digital aerial images but also other data sources is a big challenge. In this paper a novel approach for object recognition is presented based on neuro-fuzzy modelling. Structural, textural and spectral information is extracted and integrated in a fuzzy reasoning process. The learning capability of neural networks is introduced to the fuzzy recognition process by taking adaptable parameter sets into account which leads to the neuro-fuzzy approach. Object reconstruction follows recognition seamlessly by using the recognition output and the descriptors which have been extracted for recognition. A first successful application of this new ORR approach is demonstrated for the three object classes 'buildings', 'cars' and 'trees' by using aerial colour images of an urban area of the town of Engen in Germany.

  1. Recognition by Humans and Pigeons of Novel Views of 3-D Objects and Their Photographs

    ERIC Educational Resources Information Center

    Friedman, Alinda; Spetch, Marcia L.; Ferrey, Anne

    2005-01-01

    Humans and pigeons were trained to discriminate between 2 views of actual 3-D objects or their photographs. They were tested on novel views that were either within the closest rotational distance between the training views (interpolated) or outside of that range (extrapolated). When training views were 60? apart, pigeons, but not humans,…

  2. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  3. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes

    PubMed Central

    Yebes, J. Javier; Bergasa, Luis M.; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  4. 3D scene's object detection and recognition using depth layers and SIFT-based machine learning

    NASA Astrophysics Data System (ADS)

    Kounalakis, T.; Triantafyllidis, G. A.

    2011-09-01

    This paper presents a novel system that is fusing efficient and state-of-the-art techniques of stereo vision and machine learning, aiming at object detection and recognition. To this goal, the system initially creates depth maps by employing the Graph-Cut technique. Then, the depth information is used for object detection by separating the objects from the whole scene. Next, the Scale-Invariant Feature Transform (SIFT) is used, providing the system with unique object's feature key-points, which are employed in training an Artificial Neural Network (ANN). The system is then able to classify and recognize the nature of these objects, creating knowledge from the real world. [Figure not available: see fulltext.

  5. 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.

  6. 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.

  7. A roadmap to global illumination in 3D scenes: solutions for GPU object recognition applications

    NASA Astrophysics Data System (ADS)

    Picos, Kenia; Díaz-Ramírez, Victor H.; Tapia, Juan J.

    2014-09-01

    Light interactions with matter is of remarkable complexity. An adequate modeling of global illumination is a vastly studied topic since the beginning of computer graphics, and still is an unsolved problem. The rendering equation for global illumination is based of refraction and reflection of light in interaction with matter within an environment. This physical process possesses a high computational complexity when implemented in a digital computer. The appearance of an object depends on light interactions with the surface of the material, such as emission, scattering, and absorption. Several image-synthesis methods have been used to realistically render the appearance of light incidence on an object. Recent global illumination algorithms employ mathematical models and computational strategies that improve the efficiency of the simulation solution. This work presents a review the state of the art of global illumination algorithms and focuses on the efficiency of the solution in a computational implementation in a graphics processing unit. A reliable system is developed to simulate realistics scenes in the context of real-time object recognition under different lighting conditions. Computer simulations results are presented and discussed in terms of discrimination capability, and robustness to additive noise, when considering several lighting model reflections and multiple light sources.

  8. 3D Object Recognition using Gabor Feature Extraction and PCA-FLD Projections of Holographically Sensed Data

    NASA Astrophysics Data System (ADS)

    Yeom, Seokwon; Javidi, Bahram

    In this research, a 3D object classification technique using a single hologram has been presented. The PCA-FLD classifier with feature vectors based on Gabor wavelets has been utilized for this purpose. Training and test data of the 3D objects were obtained by computational holographic imaging. We were able to classify 3D objects used in the experiments with a few reconstructed planes of the hologram. The Gabor approach appears to be a good feature extractor for hologram-based 3D classification. The FLD combined with the PCA proved to be a very efficient classifier even with a few training data. Substantial dimensionality reduction was achieved by using the proposed technique for 3D classification problem using holographic imaging. As a consequence, we were able to classify different classes of 3D objects using computer-reconstructed holographic images.

  9. Lifting Object Detection Datasets into 3D.

    PubMed

    Carreira, Joao; Vicente, Sara; Agapito, Lourdes; Batista, Jorge

    2016-07-01

    While data has certainly taken the center stage in computer vision in recent years, it can still be difficult to obtain in certain scenarios. In particular, acquiring ground truth 3D shapes of objects pictured in 2D images remains a challenging feat and this has hampered progress in recognition-based object reconstruction from a single image. Here we propose to bypass previous solutions such as 3D scanning or manual design, that scale poorly, and instead populate object category detection datasets semi-automatically with dense, per-object 3D reconstructions, bootstrapped from:(i) class labels, (ii) ground truth figure-ground segmentations and (iii) a small set of keypoint annotations. Our proposed algorithm first estimates camera viewpoint using rigid structure-from-motion and then reconstructs object shapes by optimizing over visual hull proposals guided by loose within-class shape similarity assumptions. The visual hull sampling process attempts to intersect an object's projection cone with the cones of minimal subsets of other similar objects among those pictured from certain vantage points. We show that our method is able to produce convincing per-object 3D reconstructions and to accurately estimate cameras viewpoints on one of the most challenging existing object-category detection datasets, PASCAL VOC. We hope that our results will re-stimulate interest on joint object recognition and 3D reconstruction from a single image. PMID:27295458

  10. Recognition methods for 3D textured surfaces

    NASA Astrophysics Data System (ADS)

    Cula, Oana G.; Dana, Kristin J.

    2001-06-01

    Texture as a surface representation is the subject of a wide body of computer vision and computer graphics literature. While texture is always associated with a form of repetition in the image, the repeating quantity may vary. The texture may be a color or albedo variation as in a checkerboard, a paisley print or zebra stripes. Very often in real-world scenes, texture is instead due to a surface height variation, e.g. pebbles, gravel, foliage and any rough surface. Such surfaces are referred to here as 3D textured surfaces. Standard texture recognition algorithms are not appropriate for 3D textured surfaces because the appearance of these surfaces changes in a complex manner with viewing direction and illumination direction. Recent methods have been developed for recognition of 3D textured surfaces using a database of surfaces observed under varied imaging parameters. One of these methods is based on 3D textons obtained using K-means clustering of multiscale feature vectors. Another method uses eigen-analysis originally developed for appearance-based object recognition. In this work we develop a hybrid approach that employs both feature grouping and dimensionality reduction. The method is tested using the Columbia-Utrecht texture database and provides excellent recognition rates. The method is compared with existing recognition methods for 3D textured surfaces. A direct comparison is facilitated by empirical recognition rates from the same texture data set. The current method has key advantages over existing methods including requiring less prior information on both the training and novel images.

  11. 3D object retrieval using salient views.

    PubMed

    Atmosukarto, Indriyati; Shapiro, Linda G

    2013-06-01

    This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223-232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223-232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

  12. 3D object retrieval using salient views

    PubMed Central

    Shapiro, Linda G.

    2013-01-01

    This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223–232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223–232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

  13. 3D model-based still image object categorization

    NASA Astrophysics Data System (ADS)

    Petre, Raluca-Diana; Zaharia, Titus

    2011-09-01

    This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

  14. A Modified Exoskeleton for 3D Shape Description and Recognition

    NASA Astrophysics Data System (ADS)

    Lipikorn, Rajalida; Shimizu, Akinobu; Hagihara, Yoshihiro; Kobatake, Hidefumi

    Three-dimensional(3D) shape representation is a powerful tool in object recognition that is an essential process in an image processing and analysis system. Skeleton is one of the most widely used representations for object recognition, nevertheless most of the skeletons obtained from conventional methods are susceptible to rotation and noise disturbances. In this paper, we present a new 3D object representation called a modified exoskeleton (mES) which preserves skeleton properties including significant characteristics about an object that are meaningful for object recognition, and is more stable and less susceptible to rotation and noise than the skeletons. Then a 3D shape recognition methodology which determines the similarity between an observed object and other known objects in a database is introduced. Through a number of experiments on 3D artificial objects and real volumetric lung tumors extracted from CT images, it can be verified that our proposed methodology based on the mES is a simple yet efficient method that is less sensitive to rotation, noise, and independent of orientation and size of the objects.

  15. 3D gesture recognition from serial range image

    NASA Astrophysics Data System (ADS)

    Matsui, Yasuyuki; Miyasaka, Takeo; Hirose, Makoto; Araki, Kazuo

    2001-10-01

    In this research, the recognition of gesture in 3D space is examined by using serial range images obtained by a real-time 3D measurement system developed in our laboratory. Using this system, it is possible to obtain time sequences of range, intensity and color data for a moving object in real-time without assigning markers to the targets. At first, gestures are tracked in 2D space by calculating 2D flow vectors at each points using an ordinal optical flow estimation method, based on time sequences of the intensity data. Then, location of each point after 2D movement is detected on the x-y plane using thus obtained 2D flow vectors. Depth information of each point after movement is then obtained from the range data and 3D flow vectors are assigned to each point. Time sequences of thus obtained 3D flow vectors allow us to track the 3D movement of the target. So, based on time sequences of 3D flow vectors of the targets, it is possible to classify the movement of the targets using continuous DP matching technique. This tracking of 3D movement using time sequences of 3D flow vectors may be applicable for a robust gesture recognition system.

  16. Human efficiency for recognizing 3-D objects in luminance noise.

    PubMed

    Tjan, B S; Braje, W L; Legge, G E; Kersten, D

    1995-11-01

    The purpose of this study was to establish how efficiently humans use visual information to recognize simple 3-D objects. The stimuli were computer-rendered images of four simple 3-D objects--wedge, cone, cylinder, and pyramid--each rendered from 8 randomly chosen viewing positions as shaded objects, line drawings, or silhouettes. The objects were presented in static, 2-D Gaussian luminance noise. The observer's task was to indicate which of the four objects had been presented. We obtained human contrast thresholds for recognition, and compared these to an ideal observer's thresholds to obtain efficiencies. In two auxiliary experiments, we measured efficiencies for object detection and letter recognition. Our results showed that human object-recognition efficiency is low (3-8%) when compared to efficiencies reported for some other visual-information processing tasks. The low efficiency means that human recognition performance is limited primarily by factors intrinsic to the observer rather than the information content of the stimuli. We found three factors that play a large role in accounting for low object-recognition efficiency: stimulus size, spatial uncertainty, and detection efficiency. Four other factors play a smaller role in limiting object-recognition efficiency: observers' internal noise, stimulus rendering condition, stimulus familiarity, and categorization across views. PMID:8533342

  17. Random-Profiles-Based 3D Face Recognition System

    PubMed Central

    Joongrock, Kim; Sunjin, Yu; Sangyoun, Lee

    2014-01-01

    In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation. PMID:24691101

  18. 3D modeling of optically challenging objects.

    PubMed

    Park, Johnny; Kak, Avinash

    2008-01-01

    We present a system for constructing 3D models of real-world objects with optically challenging surfaces. The system utilizes a new range imaging concept called multi-peak range imaging, which stores multiple candidates of range measurements for each point on the object surface. The multiple measurements include the erroneous range data caused by various surface properties that are not ideal for structured-light range sensing. False measurements generated by spurious reflections are eliminated by applying a series of constraint tests. The constraint tests based on local surface and local sensor visibility are applied first to individual range images. The constraint tests based on global consistency of coordinates and visibility are then applied to all range images acquired from different viewpoints. We show the effectiveness of our method by constructing 3D models of five different optically challenging objects. To evaluate the performance of the constraint tests and to examine the effects of the parameters used in the constraint tests, we acquired the ground truth data by painting those objects to suppress the surface-related properties that cause difficulties in range sensing. Experimental results indicate that our method significantly improves upon the traditional methods for constructing reliable 3D models of optically challenging objects. PMID:18192707

  19. Faint object 3D spectroscopy with PMAS

    NASA Astrophysics Data System (ADS)

    Roth, Martin M.; Becker, Thomas; Kelz, Andreas; Bohm, Petra

    2004-09-01

    PMAS is a fiber-coupled lens array type of integral field spectrograph, which was commissioned at the Calar Alto 3.5m Telescope in May 2001. The optical layout of the instrument was chosen such as to provide a large wavelength coverage, and good transmission from 0.35 to 1 μm. One of the major objectives of the PMAS development has been to perform 3D spectrophotometry, taking advantage of the contiguous array of spatial elements over the 2-dimensional field-of-view of the integral field unit. With science results obtained during the first two years of operation, we illustrate that 3D spectroscopy is an ideal tool for faint object spectrophotometry.

  20. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  1. 3D palmprint data fast acquisition and recognition

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoxu; Huang, Shujun; Gao, Nan; Zhang, Zonghua

    2014-11-01

    This paper presents a fast 3D (Three-Dimension) palmprint capturing system and develops an efficient 3D palmprint feature extraction and recognition method. In order to fast acquire accurate 3D shape and texture of palmprint, a DLP projector triggers a CCD camera to realize synchronization. By generating and projecting green fringe pattern images onto the measured palm surface, 3D palmprint data are calculated from the fringe pattern images. The periodic feature vector can be derived from the calculated 3D palmprint data, so undistorted 3D biometrics is obtained. Using the obtained 3D palmprint data, feature matching test have been carried out by Gabor filter, competition rules and the mean curvature. Experimental results on capturing 3D palmprint show that the proposed acquisition method can fast get 3D shape information of palmprint. Some initial experiments on recognition show the proposed method is efficient by using 3D palmprint data.

  2. Color constancy in 3D-2D face recognition

    NASA Astrophysics Data System (ADS)

    Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.

    2013-05-01

    Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

  3. A review of recent advances in 3D face recognition

    NASA Astrophysics Data System (ADS)

    Luo, Jing; Geng, Shuze; Xiao, Zhaoxia; Xiu, Chunbo

    2015-03-01

    Face recognition based on machine vision has achieved great advances and been widely used in the various fields. However, there are some challenges on the face recognition, such as facial pose, variations in illumination, and facial expression. So, this paper gives the recent advances in 3D face recognition. 3D face recognition approaches are categorized into four groups: minutiae approach, space transform approach, geometric features approach, model approach. Several typical approaches are compared in detail, including feature extraction, recognition algorithm, and the performance of the algorithm. Finally, this paper summarized the challenge existing in 3D face recognition and the future trend. This paper aims to help the researches majoring on face recognition.

  4. 3D fast wavelet network model-assisted 3D face recognition

    NASA Astrophysics Data System (ADS)

    Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

    2015-12-01

    In last years, the emergence of 3D shape in face recognition is due to its robustness to pose and illumination changes. These attractive benefits are not all the challenges to achieve satisfactory recognition rate. Other challenges such as facial expressions and computing time of matching algorithms remain to be explored. In this context, we propose our 3D face recognition approach using 3D wavelet networks. Our approach contains two stages: learning stage and recognition stage. For the training we propose a novel algorithm based on 3D fast wavelet transform. From 3D coordinates of the face (x,y,z), we proceed to voxelization to get a 3D volume which will be decomposed by 3D fast wavelet transform and modeled after that with a wavelet network, then their associated weights are considered as vector features to represent each training face . For the recognition stage, an unknown identity face is projected on all the training WN to obtain a new vector features after every projection. A similarity score is computed between the old and the obtained vector features. To show the efficiency of our approach, experimental results were performed on all the FRGC v.2 benchmark.

  5. 3D face recognition based on matching of facial surfaces

    NASA Astrophysics Data System (ADS)

    Echeagaray-Patrón, Beatriz A.; Kober, Vitaly

    2015-09-01

    Face recognition is an important task in pattern recognition and computer vision. In this work a method for 3D face recognition in the presence of facial expression and poses variations is proposed. The method uses 3D shape data without color or texture information. A new matching algorithm based on conformal mapping of original facial surfaces onto a Riemannian manifold followed by comparison of conformal and isometric invariants computed in the manifold is suggested. Experimental results are presented using common 3D face databases that contain significant amount of expression and pose variations.

  6. Recognition technology research based on 3D fingerprint

    NASA Astrophysics Data System (ADS)

    Tian, Qianxiao; Huang, Shujun; Zhang, Zonghua

    2014-11-01

    Fingerprint has been widely studied and applied to personal recognition in both forensics and civilian. However, the current widespread used fingerprint is identified by 2D (two-dimensional) fingerprint image and the mapping from 3D (three-dimensional) to 2D loses 1D information, which leads to low accurate and even wrong recognition. This paper presents a 3D fingerprint recognition method based on the fringe projection technique. A series of fringe patterns generated by software are projected onto a finger surface through a projecting system. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. The deformed fringe pattern images give the 3D shape data of the finger and the 3D fingerprint features. Through converting the 3D fingerprints to 2D space, traditional 2D fingerprint recognition method can be used to 3D fingerprints recognition. Experimental results on measuring and recognizing some 3D fingerprints show the accuracy and availability of the developed 3D fingerprint system.

  7. PMAS - Faint Object 3D Spectrophotometry

    NASA Astrophysics Data System (ADS)

    Roth, M. M.; Becker, T.; Kelz, A.

    2002-01-01

    will describe PMAS (Potsdam Multiaperture Spectrophotometer) which was commissioned at the Calar Alto Observatory 3.5m Telescope on May 28-31, 2001. PMAS is a dedicated, highly efficient UV-visual integral field spectrograph which is optimized for the spectrophotometry of faint point sources, typically superimposed on a bright background. PMAS is ideally suited for the study of resolved stars in local group galaxies. I will present results of our preliminary work with MPFS at the Russian 6m Telescope in Selentchuk, involving the development of new 3D data reduction software, and observations of faint planetary nebulae in the bulge of M31 for the determination of individual chemical abundances of these objects. Using this data, it will be demonstrated that integral field spectroscopy provides superior techniques for background subtraction, avoiding the otherwise inevitable systematic errors of conventional slit spetroscopy. The results will be put in perspective of the study of resolved stellar populations in nearby galaxies with a new generation of Extremely Large Telescopes.

  8. Personal perceptual and cognitive property for 3D recognition

    NASA Astrophysics Data System (ADS)

    Matozaki, Takeshi; Tanisita, Akihiko

    1996-04-01

    3D closed circuit TV which produces stereoscopic vision by observing different images through each eye alternately, has been proposed. But, there are several problems, both physiological and psychological, for 3D image observation in many fields. From this prospective, we are learning personal visual characteristics for 3D recognition in the transition from 2D to 3D. We have separated the mechanism of 3D recognition into several categories, and formed some hypothesis about the personal features. These hypotheses are related to an observer's personal features, as follows: (1) consideration of the angle between the left and the right eye's line of vision and the adjustment of focus, (2) consideration of the angle of vision and the time required for fusion, (3) consideration of depth sense based on life experience, (4) consideration of 3D experience, and (5) consideration of 3D sense based on the observer's age. To establish these hypotheses, and we have analyzed the personal features of the time interval required for 3D recognition through some examinations to examinees. Examinees indicate their response for 3D recognition by pushing a button. Recently, we introduced a method for picking up the reaction of 3D recognition from examinees through their biological information, for example, analysis of pulse waves of the finger. We also bring a hypothesis, as a result of the analysis of pulse waves. (1) We can observe chaotic response when the examinee is recognizing a 2D image. (2) We can observe periodic response when the examinee is recognizing a 3D image. We are making nonlinear forecasts by getting correlation between the forecast and the biological phenomena. Deterministic nonlinear prediction are applied to the data, as a promising method of chaotic time series analysis in order to analyze the long term unpredictability, one of the fundamental characteristics of deterministic chaos.

  9. Visual inertia of rotating 3-D objects.

    PubMed

    Jiang, Y; Pantle, A J; Mark, L S

    1998-02-01

    Five experiments were designed to determine whether a rotating, transparent 3-D cloud of dots (simulated sphere) could influence the perceived direction of rotation of a subsequent sphere. Experiment 1 established conditions under which the direction of rotation of a virtual sphere was perceived unambiguously. When a near-far luminance difference and perspective depth cues were present, observers consistently saw the sphere rotate in the intended direction. In Experiment 2, a near-far luminance difference was used to create an unambiguous rotation sequence that was followed by a directionally ambiguous rotation sequence that lacked both the near-far luminance cue and the perspective cue. Observers consistently saw the second sequence as rotating in the same direction as the first, indicating the presence of 3-D visual inertia. Experiment 3 showed that 3-D visual inertia was sufficiently powerful to bias the perceived direction of a rotation sequence made unambiguous by a near-far luminance cue. Experiment 5 showed that 3-D visual inertia could be obtained using an occlusion depth cue to create an unambiguous inertia-inducing sequence. Finally, Experiments 2, 4, and 5 all revealed a fast-decay phase of inertia that lasted for approximately 800 msec, followed by an asymptotic phase that lasted for periods as long as 1,600 msec. The implications of these findings are examined with respect to motion mechanisms of 3-D visual inertia. PMID:9529911

  10. Hough-based recognition of complex 3-D road scenes

    NASA Astrophysics Data System (ADS)

    Foresti, Gian L.; Regazzoni, Carlo S.

    1992-02-01

    In this paper, we address the problem of the object recognition in a complex 3-D scene by detecting the 2-D object projection on the image-plane for an autonomous vehicle driving; in particular, the problems of road detection and obstacle avoidance in natural road scenes are investigated. A new implementation of the Hough Transform (HT), called Labeled Hough Transform (LHT), to extract and group symbolic features is here presented; the novelty of this method, in respect to the traditional approach, consists in the capability of splitting a maximum in the parameter space into noncontiguous segments, while performing voting. Results are presented on a road image containing obstacles which show the efficiency, good quality, and time performances of the algorithm.

  11. The use of 3D information in face recognition.

    PubMed

    Liu, Chang Hong; Ward, James

    2006-03-01

    Effects of shading in face recognition have often alluded to 3D shape processing. However, research to date has failed to demonstrate any use of important 3D information. Stereopsis adds no advantage in face encoding [Liu, C. H., Ward, J., & Young, A. W. (in press). Transfer between 2D and 3D representations of faces. Visual Cognition], and perspective transformation impairs rather than assists recognition performance [Liu, C. H. (2003). Is face recognition in pictures affected by the center of projection? In IEEE international workshop on analysis and modeling of faces and gestures (pp. 53-59). Nice, France: IEEE Computer Society]. Although evidence tends to rule out involvement of 3D information in face processing, it remains possible that the usefulness of this information depends on certain combinations of cues. We tested this hypothesis in a recognition task, where face stimuli with several levels of perspective transformation were either presented in stereo or without stereo. We found that even at a moderate level of perspective transformation where training and test faces were separated by just 30 cm, the stereo condition produced better performance. This provides the first evidence that stereo information can facilitate face recognition. We conclude that 3D information plays a role in face processing but only when certain types of 3D cues are properly combined. PMID:16298412

  12. Automatic object recognition

    NASA Technical Reports Server (NTRS)

    Ranganath, H. S.; Mcingvale, Pat; Sage, Heinz

    1988-01-01

    Geometric and intensity features are very useful in object recognition. An intensity feature is a measure of contrast between object pixels and background pixels. Geometric features provide shape and size information. A model based approach is presented for computing geometric features. Knowledge about objects and imaging system is used to estimate orientation of objects with respect to the line of sight.

  13. Lateralized Effects of Categorical and Coordinate Spatial Processing of Component Parts on the Recognition of 3D Non-Nameable Objects

    ERIC Educational Resources Information Center

    Saneyoshi, Ayako; Michimata, Chikashi

    2009-01-01

    Participants performed two object-matching tasks for novel, non-nameable objects consisting of geons. For each original stimulus, two transformations were applied to create comparison stimuli. In the categorical transformation, a geon connected to geon A was moved to geon B. In the coordinate transformation, a geon connected to geon A was moved to…

  14. Rapid 360 degree imaging and stitching of 3D objects using multiple precision 3D cameras

    NASA Astrophysics Data System (ADS)

    Lu, Thomas; Yin, Stuart; Zhang, Jianzhong; Li, Jiangan; Wu, Frank

    2008-02-01

    In this paper, we present the system architecture of a 360 degree view 3D imaging system. The system consists of multiple 3D sensors synchronized to take 3D images around the object. Each 3D camera employs a single high-resolution digital camera and a color-coded light projector. The cameras are synchronized to rapidly capture the 3D and color information of a static object or a live person. The color encoded structure lighting ensures the precise reconstruction of the depth of the object. A 3D imaging system architecture is presented. The architecture employs the displacement of the camera and the projector to triangulate the depth information. The 3D camera system has achieved high depth resolution down to 0.1mm on a human head sized object and 360 degree imaging capability.

  15. 3D face recognition based on a modified ICP method

    NASA Astrophysics Data System (ADS)

    Zhao, Kankan; Xi, Jiangtao; Yu, Yanguang; Chicharo, Joe F.

    2011-11-01

    3D face recognition technique has gained much more attention recently, and it is widely used in security system, identification system, and access control system, etc. The core technique in 3D face recognition is to find out the corresponding points in different 3D face images. The classic partial Iterative Closest Point (ICP) method is iteratively align the two point sets based on repetitively calculate the closest points as the corresponding points in each iteration. After several iterations, the corresponding points can be obtained accurately. However, if two 3D face images with different scale are from the same person, the classic partial ICP does not work. In this paper we propose a modified partial Iterative Closest Point (ICP) method in which the scaling effect is considered to achieve 3D face recognition. We design a 3x3 diagonal matrix as the scale matrix in each iteration of the classic partial ICP. The probing face image which is multiplied by the scale matrix will keep the similar scale with the reference face image. Therefore, we can accurately determine the corresponding points even the scales of probing image and reference image are different. 3D face images in our experiments are acquired by a 3D data acquisition system based on Digital Fringe Projection Profilometry (DFPP). A 3D database consists of 30 group images, three images with the same scale, which are from the same person with different views, are included in each group. And in different groups, the scale of the 3 images may be different from other groups. The experiment results show that our proposed method can achieve 3D face recognition, especially in the case that the scales of probing image and referent image are different.

  16. Photon-counting passive 3D image sensing and processing for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Yeom, Seokwon; Javidi, Bahram; Watson, Edward

    2008-04-01

    In this paper we overview the nonlinear matched filtering for photon counting recognition with 3D passive sensing. The first and second order statistical properties of the nonlinear matched filtering can improve the recognition performance compared to the linear matched filtering. Automatic target reconstruction and recognition are addressed for partially occluded objects. The recognition performance is shown to be improved significantly in the reconstruction space. The discrimination capability is analyzed in terms of Fisher ratio (FR) and receiver operating characteristic (ROC) curves.

  17. 3D ladar ATR based on recognition by parts

    NASA Astrophysics Data System (ADS)

    Sobel, Erik; Douglas, Joel; Ettinger, Gil

    2003-09-01

    LADAR imaging is unique in its potential to accurately measure the 3D surface geometry of targets. We exploit this 3D geometry to perform automatic target recognition on targets in the domain of military and civilian ground vehicles. Here we present a robust model based 3D LADAR ATR system which efficiently searches through target hypothesis space by reasoning hierarchically from vehicle parts up to identification of a whole vehicle with specific pose and articulation state. The LADAR data consists of one or more 3D point clouds generated by laser returns from ground vehicles viewed from multiple sensor locations. The key to this approach is an automated 3D registration process to precisely align and match multiple data views to model based predictions of observed LADAR data. We accomplish this registration using robust 3D surface alignment techniques which we have also used successfully in 3D medical image analysis applications. The registration routine seeks to minimize a robust 3D surface distance metric to recover the best six-degree-of-freedom pose and fit. We process the observed LADAR data by first extracting salient parts, matching these parts to model based predictions and hierarchically constructing and testing increasingly detailed hypotheses about the identity of the observed target. This cycle of prediction, extraction, and matching efficiently partitions the target hypothesis space based on the distinctive anatomy of the target models and achieves effective recognition by progressing logically from a target's constituent parts up to its complete pose and articulation state.

  18. 3D PDF - a means of public access to geological 3D - objects, using the example of GTA3D

    NASA Astrophysics Data System (ADS)

    Slaby, Mark-Fabian; Reimann, Rüdiger

    2013-04-01

    In geology, 3D modeling has become very important. In the past, two-dimensional data such as isolines, drilling profiles, or cross-sections based on those, were used to illustrate the subsurface geology, whereas now, we can create complex digital 3D models. These models are produced with special software, such as GOCAD ®. The models can be viewed, only through the software used to create them, or through viewers available for free. The platform-independent PDF (Portable Document Format), enforced by Adobe, has found a wide distribution. This format has constantly evolved over time. Meanwhile, it is possible to display CAD data in an Adobe 3D PDF file with the free Adobe Reader (version 7). In a 3D PDF, a 3D model is freely rotatable and can be assembled from a plurality of objects, which can thus be viewed from all directions on their own. In addition, it is possible to create moveable cross-sections (profiles), and to assign transparency to the objects. Based on industry-standard CAD software, 3D PDFs can be generated from a large number of formats, or even be exported directly from this software. In geoinformatics, different approaches to creating 3D PDFs exist. The intent of the Authority for Mining, Energy and Geology to allow free access to the models of the Geotectonic Atlas (GTA3D), could not be realized with standard software solutions. A specially designed code converts the 3D objects to VRML (Virtual Reality Modeling Language). VRML is one of the few formats that allow using image files (maps) as textures, and to represent colors and shapes correctly. The files were merged in Acrobat X Pro, and a 3D PDF was generated subsequently. A topographic map, a display of geographic directions and horizontal and vertical scales help to facilitate the use.

  19. Interactive photogrammetric system for mapping 3D objects

    NASA Astrophysics Data System (ADS)

    Knopp, Dave E.

    1990-08-01

    A new system, FOTO-G, has been developed for 3D photogrammetric applications. It is a production-oriented software system designed to work with highly unconventional photogrammetric image configurations which result when photographing 3D objects. A demonstration with imagery from an actual 3D-mapping project is reported.

  20. Objective and subjective quality assessment of geometry compression of reconstructed 3D humans in a 3D virtual room

    NASA Astrophysics Data System (ADS)

    Mekuria, Rufael; Cesar, Pablo; Doumanis, Ioannis; Frisiello, Antonella

    2015-09-01

    Compression of 3D object based video is relevant for 3D Immersive applications. Nevertheless, the perceptual aspects of the degradation introduced by codecs for meshes and point clouds are not well understood. In this paper we evaluate the subjective and objective degradations introduced by such codecs in a state of art 3D immersive virtual room. In the 3D immersive virtual room, users are captured with multiple cameras, and their surfaces are reconstructed as photorealistic colored/textured 3D meshes or point clouds. To test the perceptual effect of compression and transmission, we render degraded versions with different frame rates in different contexts (near/far) in the scene. A quantitative subjective study with 16 users shows that negligible distortion of decoded surfaces compared to the original reconstructions can be achieved in the 3D virtual room. In addition, a qualitative task based analysis in a full prototype field trial shows increased presence, emotion, user and state recognition of the reconstructed 3D Human representation compared to animated computer avatars.

  1. Learning the spherical harmonic features for 3-D face recognition.

    PubMed

    Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

    2013-03-01

    In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method. PMID:23060332

  2. Iterative closest normal point for 3D face recognition.

    PubMed

    Mohammadzade, Hoda; Hatzinakos, Dimitrios

    2013-02-01

    The common approach for 3D face recognition is to register a probe face to each of the gallery faces and then calculate the sum of the distances between their points. This approach is computationally expensive and sensitive to facial expression variation. In this paper, we introduce the iterative closest normal point method for finding the corresponding points between a generic reference face and every input face. The proposed correspondence finding method samples a set of points for each face, denoted as the closest normal points. These points are effectively aligned across all faces, enabling effective application of discriminant analysis methods for 3D face recognition. As a result, the expression variation problem is addressed by minimizing the within-class variability of the face samples while maximizing the between-class variability. As an important conclusion, we show that the surface normal vectors of the face at the sampled points contain more discriminatory information than the coordinates of the points. We have performed comprehensive experiments on the Face Recognition Grand Challenge database, which is presently the largest available 3D face database. We have achieved verification rates of 99.6 and 99.2 percent at a false acceptance rate of 0.1 percent for the all versus all and ROC III experiments, respectively, which, to the best of our knowledge, have seven and four times less error rates, respectively, compared to the best existing methods on this database. PMID:22585097

  3. 3D Multi-Spectrum Sensor System with Face Recognition

    PubMed Central

    Kim, Joongrock; Yu, Sunjin; Kim, Ig-Jae; Lee, Sangyoun

    2013-01-01

    This paper presents a novel three-dimensional (3D) multi-spectrum sensor system, which combines a 3D depth sensor and multiple optical sensors for different wavelengths. Various image sensors, such as visible, infrared (IR) and 3D sensors, have been introduced into the commercial market. Since each sensor has its own advantages under various environmental conditions, the performance of an application depends highly on selecting the correct sensor or combination of sensors. In this paper, a sensor system, which we will refer to as a 3D multi-spectrum sensor system, which comprises three types of sensors, visible, thermal-IR and time-of-flight (ToF), is proposed. Since the proposed system integrates information from each sensor into one calibrated framework, the optimal sensor combination for an application can be easily selected, taking into account all combinations of sensors information. To demonstrate the effectiveness of the proposed system, a face recognition system with light and pose variation is designed. With the proposed sensor system, the optimal sensor combination, which provides new effectively fused features for a face recognition system, is obtained. PMID:24072025

  4. 3D multi-spectrum sensor system with face recognition.

    PubMed

    Kim, Joongrock; Yu, Sunjin; Kim, Ig-Jae; Lee, Sangyoun

    2013-01-01

    This paper presents a novel three-dimensional (3D) multi-spectrum sensor system, which combines a 3D depth sensor and multiple optical sensors for different wavelengths. Various image sensors, such as visible, infrared (IR) and 3D sensors, have been introduced into the commercial market. Since each sensor has its own advantages under various environmental conditions, the performance of an application depends highly on selecting the correct sensor or combination of sensors. In this paper, a sensor system, which we will refer to as a 3D multi-spectrum sensor system, which comprises three types of sensors, visible, thermal-IR and time-of-flight (ToF), is proposed. Since the proposed system integrates information from each sensor into one calibrated framework, the optimal sensor combination for an application can be easily selected, taking into account all combinations of sensors information. To demonstrate the effectiveness of the proposed system, a face recognition system with light and pose variation is designed. With the proposed sensor system, the optimal sensor combination, which provides new effectively fused features for a face recognition system, is obtained. PMID:24072025

  5. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D

    2005-02-04

    Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.

  6. 3-D object-oriented image analysis of geophysical data

    NASA Astrophysics Data System (ADS)

    Fadel, I.; Kerle, N.; van der Meijde, M.

    2014-07-01

    Geophysical data are the main source of information about the subsurface. Geophysical techniques are, however, highly non-unique in determining specific physical parameters and boundaries of subsurface objects. To obtain actual physical information, an inversion process is often applied, in which measurements at or above the Earth surface are inverted into a 2- or 3-D subsurface spatial distribution of the physical property. Interpreting these models into structural objects, related to physical processes, requires a priori knowledge and expert analysis which is susceptible to subjective choices and is therefore often non-repeatable. In this research, we implemented a recently introduced object-based approach to interpret the 3-D inversion results of a single geophysical technique using the available a priori information and the physical and geometrical characteristics of the interpreted objects. The introduced methodology is semi-automatic and repeatable, and allows the extraction of subsurface structures using 3-D object-oriented image analysis (3-D OOA) in an objective knowledge-based classification scheme. The approach allows for a semi-objective setting of thresholds that can be tested and, if necessary, changed in a very fast and efficient way. These changes require only changing the thresholds used in a so-called ruleset, which is composed of algorithms that extract objects from a 3-D data cube. The approach is tested on a synthetic model, which is based on a priori knowledge on objects present in the study area (Tanzania). Object characteristics and thresholds were well defined in a 3-D histogram of velocity versus depth, and objects were fully retrieved. The real model results showed how 3-D OOA can deal with realistic 3-D subsurface conditions in which the boundaries become fuzzy, the object extensions become unclear and the model characteristics vary with depth due to the different physical conditions. As expected, the 3-D histogram of the real data was

  7. Aesthetic preference recognition of 3D shapes using EEG.

    PubMed

    Chew, Lin Hou; Teo, Jason; Mountstephens, James

    2016-04-01

    Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time-frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike. PMID:27066153

  8. An Evaluative Review of Simulated Dynamic Smart 3d Objects

    NASA Astrophysics Data System (ADS)

    Romeijn, H.; Sheth, F.; Pettit, C. J.

    2012-07-01

    Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.

  9. 3D laser imaging for concealed object identification

    NASA Astrophysics Data System (ADS)

    Berechet, Ion; Berginc, Gérard; Berechet, Stefan

    2014-09-01

    This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

  10. A 2D range Hausdorff approach for 3D face recognition.

    SciTech Connect

    Koch, Mark William; Russ, Trina Denise; Little, Charles Quentin

    2005-04-01

    This paper presents a 3D facial recognition algorithm based on the Hausdorff distance metric. The standard 3D formulation of the Hausdorff matching algorithm has been modified to operate on a 2D range image, enabling a reduction in computation from O(N2) to O(N) without large storage requirements. The Hausdorff distance is known for its robustness to data outliers and inconsistent data between two data sets, making it a suitable choice for dealing with the inherent problems in many 3D datasets due to sensor noise and object self-occlusion. For optimal performance, the algorithm assumes a good initial alignment between probe and template datasets. However, to minimize the error between two faces, the alignment can be iteratively refined. Results from the algorithm are presented using 3D face images from the Face Recognition Grand Challenge database version 1.0.

  11. A 2D range Hausdorff approach to 3D facial recognition.

    SciTech Connect

    Koch, Mark William; Russ, Trina Denise; Little, Charles Quentin

    2004-11-01

    This paper presents a 3D facial recognition algorithm based on the Hausdorff distance metric. The standard 3D formulation of the Hausdorff matching algorithm has been modified to operate on a 2D range image, enabling a reduction in computation from O(N2) to O(N) without large storage requirements. The Hausdorff distance is known for its robustness to data outliers and inconsistent data between two data sets, making it a suitable choice for dealing with the inherent problems in many 3D datasets due to sensor noise and object self-occlusion. For optimal performance, the algorithm assumes a good initial alignment between probe and template datasets. However, to minimize the error between two faces, the alignment can be iteratively refined. Results from the algorithm are presented using 3D face images from the Face Recognition Grand Challenge database version 1.0.

  12. 3D measurement of human upper body for gesture recognition

    NASA Astrophysics Data System (ADS)

    Wan, Khairunizam; Sawada, Hideyuki

    2007-10-01

    Measurement of human motion is widely required for various applications, and a significant part of this task is to identify motion in the process of human motion recognition. There are several application purposes of doing this research such as in surveillance, entertainment, medical treatment and traffic applications as user interfaces that require the recognition of different parts of human body to identify an action or a motion. The most challenging task in human motion recognition is to achieve the ability and reliability of a motion capture system for tracking and recognizing dynamic movements, because human body structure has many degrees of freedom. Many attempts for recognizing body actions have been reported so far, in which gestural motions have to be measured by some sensors first, and the obtained data are processed in a computer. This paper introduces the 3D motion analysis of human upper body using an optical motion capture system for the purpose of gesture recognition. In this study, the image processing technique to track optical markers attached at feature points of human body is introduced for constructing a human upper body model and estimating its three dimensional motion.

  13. Embedding objects during 3D printing to add new functionalities.

    PubMed

    Yuen, Po Ki

    2016-07-01

    A novel method for integrating and embedding objects to add new functionalities during 3D printing based on fused deposition modeling (FDM) (also known as fused filament fabrication or molten polymer deposition) is presented. Unlike typical 3D printing, FDM-based 3D printing could allow objects to be integrated and embedded during 3D printing and the FDM-based 3D printed devices do not typically require any post-processing and finishing. Thus, various fluidic devices with integrated glass cover slips or polystyrene films with and without an embedded porous membrane, and optical devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber were 3D printed to demonstrate the versatility of the FDM-based 3D printing and embedding method. Fluid perfusion flow experiments with a blue colored food dye solution were used to visually confirm fluid flow and/or fluid perfusion through the embedded porous membrane in the 3D printed fluidic devices. Similar to typical 3D printed devices, FDM-based 3D printed devices are translucent at best unless post-polishing is performed and optical transparency is highly desirable in any fluidic devices; integrated glass cover slips or polystyrene films would provide a perfect optical transparent window for observation and visualization. In addition, they also provide a compatible flat smooth surface for biological or biomolecular applications. The 3D printed fluidic devices with an embedded porous membrane are applicable to biological or chemical applications such as continuous perfusion cell culture or biocatalytic synthesis but without the need for any post-device assembly and finishing. The 3D printed devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber would have applications in display, illumination, or optical applications. Furthermore, the FDM-based 3D printing and embedding method could also be utilized to print casting molds with an integrated glass bottom for polydimethylsiloxane (PDMS) device replication

  14. Conformal geometry and its applications on 3D shape matching, recognition, and stitching.

    PubMed

    Wang, Sen; Wang, Yang; Jin, Miao; Gu, Xianfeng David; Samaras, Dimitris

    2007-07-01

    Three-dimensional shape matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition, and classification. However, shape matching with noise, occlusion, and clutter is a challenging problem. In this paper, we analyze a family of quasi-conformal maps including harmonic maps, conformal maps, and least-squares conformal maps with regards to 3D shape matching. As a result, we propose a novel and computationally efficient shape matching framework by using least-squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D shape-matching problem to a 2D image-matching problem, by comparing the resulting 2D parametric maps, which are stable, insensitive to resolution changes and robust to occlusion, and noise. Therefore, highly accurate and efficient 3D shape matching algorithms can be achieved by using the above three parametric maps. Finally, the robustness of least-squares conformal maps is evaluated and analyzed comprehensively in 3D shape matching with occlusion, noise, and resolution variation. In order to further demonstrate the performance of our proposed method, we also conduct a series of experiments on two computer vision applications, i.e., 3D face recognition and 3D nonrigid surface alignment and stitching. PMID:17496378

  15. Tomographic compressive holographic reconstruction of 3D objects

    NASA Astrophysics Data System (ADS)

    Nehmetallah, G.; Williams, L.; Banerjee, P. P.

    2012-10-01

    Compressive holography with multiple projection tomography is applied to solve the inverse ill-posed problem of reconstruction of 3D objects with high axial accuracy. To visualize the 3D shape, we propose Digital Tomographic Compressive Holography (DiTCH), where projections from more than one direction as in tomographic imaging systems can be employed, so that a 3D shape with better axial resolution can be reconstructed. We compare DiTCH with single-beam holographic tomography (SHOT) which is based on Fresnel back-propagation. A brief theory of DiTCH is presented, and experimental results of 3D shape reconstruction of objects using DITCH and SHOT are compared.

  16. Algorithms for Haptic Rendering of 3D Objects

    NASA Technical Reports Server (NTRS)

    Basdogan, Cagatay; Ho, Chih-Hao; Srinavasan, Mandayam

    2003-01-01

    Algorithms have been developed to provide haptic rendering of three-dimensional (3D) objects in virtual (that is, computationally simulated) environments. The goal of haptic rendering is to generate tactual displays of the shapes, hardnesses, surface textures, and frictional properties of 3D objects in real time. Haptic rendering is a major element of the emerging field of computer haptics, which invites comparison with computer graphics. We have already seen various applications of computer haptics in the areas of medicine (surgical simulation, telemedicine, haptic user interfaces for blind people, and rehabilitation of patients with neurological disorders), entertainment (3D painting, character animation, morphing, and sculpting), mechanical design (path planning and assembly sequencing), and scientific visualization (geophysical data analysis and molecular manipulation).

  17. Key techniques for vision measurement of 3D object surface

    NASA Astrophysics Data System (ADS)

    Yang, Huachao; Zhang, Shubi; Guo, Guangli; Liu, Chao; Yu, Ruipeng

    2006-11-01

    Digital close-range photogrammetry system and machine vision are widely used in production control, quality inspection. The main aim is to provide accurate 3D objects or reconstruction of an object surface and give an expression to an object shape. First, the key techniques of camera calibration and target image positioning for 3D object surface vision measurement were briefly reviewed and analyzed in this paper. Then, an innovative and effect method for precise space coordinates measurements was proposed. Test research proved that the thought and methods we proposed about image segmentation, detection and positioning of circular marks were effective and valid. A propriety weight value for adding parameters, control points and orientation elements in bundle adjustment with self-calibration are advantageous to gaining high accuracy of space coordinates. The RMS error of check points is less than +/-1 mm, which can meet the requirement in industrial measurement with high accuracy.

  18. Viewpoint independent representation and recognition of polygonal faced in 3-D

    SciTech Connect

    Bunke, H.; Glauser, T.

    1993-08-01

    The recognition of polygons in 3-D space is an important task in robot vision. Two particular problems are addressed in the paper. First a new set of local shape descriptors for polygons are proposed that are invariant under affine transformation. Furthermore, they are complete in the sense that they allow the reconstruction of any polygon in 3-D space from three consecutive vertices. The second problem discussed in this paper is the recognition of 2-D polygonal objects under affine transformation and the presence of partial occlusion. A recognition procedure that is based on the matching of edge length ratios is introduced using a simplified version of the standard dynamic programming procedure commonly employed for string matching. The algorithm is conceptually very simple, easy to implement and has a low computational complexity. It will be shown in a set of experiments that the method is reliable and robust.

  19. OB3D, a new set of 3D objects available for research: a web-based study

    PubMed Central

    Buffat, Stéphane; Chastres, Véronique; Bichot, Alain; Rider, Delphine; Benmussa, Frédéric; Lorenceau, Jean

    2014-01-01

    Studying object recognition is central to fundamental and clinical research on cognitive functions but suffers from the limitations of the available sets that cannot always be modified and adapted to meet the specific goals of each study. We here present a new set of 3D scans of real objects available on-line as ASCII files, OB3D. These files are lists of dots, each defined by a triplet of spatial coordinates and their normal that allow simple and highly versatile transformations and adaptations. We performed a web-based experiment to evaluate the minimal number of dots required for the denomination and categorization of these objects, thus providing a reference threshold. We further analyze several other variables derived from this data set, such as the correlations with object complexity. This new stimulus set, which was found to activate the Lower Occipital Complex (LOC) in another study, may be of interest for studies of cognitive functions in healthy participants and patients with cognitive impairments, including visual perception, language, memory, etc. PMID:25339920

  20. 3D automatic anatomy recognition based on iterative graph-cut-ASM

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

    We call the computerized assistive process of recognizing, delineating, and quantifying organs and tissue regions in medical imaging, occurring automatically during clinical image interpretation, automatic anatomy recognition (AAR). The AAR system we are developing includes five main parts: model building, object recognition, object delineation, pathology detection, and organ system quantification. In this paper, we focus on the delineation part. For the modeling part, we employ the active shape model (ASM) strategy. For recognition and delineation, we integrate several hybrid strategies of combining purely image based methods with ASM. In this paper, an iterative Graph-Cut ASM (IGCASM) method is proposed for object delineation. An algorithm called GC-ASM was presented at this symposium last year for object delineation in 2D images which attempted to combine synergistically ASM and GC. Here, we extend this method to 3D medical image delineation. The IGCASM method effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. We propose a new GC cost function, which effectively integrates the specific image information with the ASM shape model information. The proposed methods are tested on a clinical abdominal CT data set. The preliminary results show that: (a) it is feasible to explicitly bring prior 3D statistical shape information into the GC framework; (b) the 3D IGCASM delineation method improves on ASM and GC and can provide practical operational time on clinical images.

  1. The Visual Priming of Motion-Defined 3D Objects

    PubMed Central

    Jiang, Xiong; Jiang, Yang

    2015-01-01

    The perception of a stimulus can be influenced by previous perceptual experience, a phenomenon known as perceptual priming. However, there has been limited investigation on perceptual priming of shape perception of three-dimensional object structures defined by moving dots. Here we examined the perceptual priming of a 3D object shape defined purely by motion-in-depth cues (i.e., Shape-From-Motion, SFM) using a classic prime-target paradigm. The results from the first two experiments revealed a significant increase in accuracy when a “cloudy” SFM stimulus (whose object structure was difficult to recognize due to the presence of strong noise) was preceded by an unambiguous SFM that clearly defined the same transparent 3D shape. In contrast, results from Experiment 3 revealed no change in accuracy when a “cloudy” SFM stimulus was preceded by a static shape or a semantic word that defined the same object shape. Instead, there was a significant decrease in accuracy when preceded by a static shape or a semantic word that defined a different object shape. These results suggested that the perception of a noisy SFM stimulus can be facilitated by a preceding unambiguous SFM stimulus—but not a static image or a semantic stimulus—that defined the same shape. The potential neural and computational mechanisms underlying the difference in priming are discussed. PMID:26658496

  2. Large-scale objective phenotyping of 3D facial morphology

    PubMed Central

    Hammond, Peter; Suttie, Michael

    2012-01-01

    Abnormal phenotypes have played significant roles in the discovery of gene function, but organized collection of phenotype data has been overshadowed by developments in sequencing technology. In order to study phenotypes systematically, large-scale projects with standardized objective assessment across populations are considered necessary. The report of the 2006 Human Variome Project meeting recommended documentation of phenotypes through electronic means by collaborative groups of computational scientists and clinicians using standard, structured descriptions of disease-specific phenotypes. In this report, we describe progress over the past decade in 3D digital imaging and shape analysis of the face, and future prospects for large-scale facial phenotyping. Illustrative examples are given throughout using a collection of 1107 3D face images of healthy controls and individuals with a range of genetic conditions involving facial dysmorphism. PMID:22434506

  3. 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.

  4. Three-dimensional object recognition using wavelets for feature denoising

    NASA Astrophysics Data System (ADS)

    Kim, Sung-Soo; Kasparis, Takis; Schiavone, Guy A.

    1996-06-01

    Recognition of 3D objects independent of size, position, and rotation is an important and difficult subject in computer vision. A 3D feature extraction method referred to as the Open Ball Operator (OBO) is proposed as an approach to solving the 3D object recognition problem. The OBO feature extraction method has the three characteristics of invariance to rotation, scaling, and translation invariance. Additionally, the OBO is capable of distinguishing between convexities and concavities in the surface of 3D object. The OBO also exhibits a good robustness to noise and uncertainty caused by inaccuracies in 3D measurements. A wavelet de- noising method is used for filtering out noise contained in the feature vectors of 3D objects.

  5. Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features

    PubMed Central

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694

  6. Recognizing objects in 3D point clouds with multi-scale local features.

    PubMed

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694

  7. Automated full-3D shape measurement of cultural heritage objects

    NASA Astrophysics Data System (ADS)

    Sitnik, Robert; Karaszewski, Maciej; Zaluski, Wojciech; Bolewicki, Pawel

    2009-07-01

    In this paper a fully automated 3D shape measurement system is presented. It consists of rotary stage for cultural heritage objects placement, vertical linear stage with mounted robot arm (with six degrees of freedom) and structured light measurement set-up mounted to its head. All these manipulation devices are automatically controlled by collision detection and next-best-view calculation modules. The goal of whole system is to automatically (without any user attention) and rapidly (from days and weeks to hours) measure whole object. Measurement head is automatically calibrated by the system and its possible working volume starts from centimeters and ends up to one meter. We present some measurement results with different working scenarios along with discussion about its possible applications.

  8. Fully automatic 3D digitization of unknown objects

    NASA Astrophysics Data System (ADS)

    Rozenwald, Gabriel F.; Seulin, Ralph; Fougerolle, Yohan D.

    2010-01-01

    This paper presents a complete system for 3D digitization of objects assuming no prior knowledge on its shape. The proposed methodology is applied to a digitization cell composed of a fringe projection scanner head, a robotic arm with 6 degrees of freedom (DoF), and a turntable. A two-step approach is used to automatically guide the scanning process. The first step uses the concept of Mass Vector Chains (MVC) to perform an initial scanning. The second step directs the scanner to remaining holes of the model. Post-processing of the data is also addressed. Tests with real objects were performed and results of digitization length in time and number of views are provided along with estimated surface coverage.

  9. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D W; Eppler, W G; Poland, D N

    2005-02-18

    A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.

  10. Object recognition memory in zebrafish.

    PubMed

    May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

    2016-01-01

    The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour. PMID:26376244

  11. Large distance 3D imaging of hidden objects

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon Akram, Avihai; Kopeika, N. S.; Abramovich, A.; Levanon, Assaf

    2014-06-01

    Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.

  12. The Role of Active Exploration of 3D Face Stimuli on Recognition Memory of Facial Information

    ERIC Educational Resources Information Center

    Liu, Chang Hong; Ward, James; Markall, Helena

    2007-01-01

    Research on face recognition has mainly relied on methods in which observers are relatively passive viewers of face stimuli. This study investigated whether active exploration of three-dimensional (3D) face stimuli could facilitate recognition memory. A standard recognition task and a sequential matching task were employed in a yoked design.…

  13. 3-D Interpolation in Object Perception: Evidence from an Objective Performance Paradigm

    ERIC Educational Resources Information Center

    Kellman, Philip J.; Garrigan, Patrick; Shipley, Thomas F.; Yin, Carol; Machado, Liana

    2005-01-01

    Object perception requires interpolation processes that connect visible regions despite spatial gaps. Some research has suggested that interpolation may be a 3-D process, but objective performance data and evidence about the conditions leading to interpolation are needed. The authors developed an objective performance paradigm for testing 3-D…

  14. Identification and Detection of Simple 3D Objects with Severely Blurred Vision

    PubMed Central

    Kallie, Christopher S.; Legge, Gordon E.; Yu, Deyue

    2012-01-01

    Purpose. Detecting and recognizing three-dimensional (3D) objects is an important component of the visual accessibility of public spaces for people with impaired vision. The present study investigated the impact of environmental factors and object properties on the recognition of objects by subjects who viewed physical objects with severely reduced acuity. Methods. The experiment was conducted in an indoor testing space. We examined detection and identification of simple convex objects by normally sighted subjects wearing diffusing goggles that reduced effective acuity to 20/900. We used psychophysical methods to examine the effect on performance of important environmental variables: viewing distance (from 10–24 feet, or 3.05–7.32 m) and illumination (overhead fluorescent and artificial window), and object variables: shape (boxes and cylinders), size (heights from 2–6 feet, or 0.61–1.83 m), and color (gray and white). Results. Object identification was significantly affected by distance, color, height, and shape, as well as interactions between illumination, color, and shape. A stepwise regression analysis showed that 64% of the variability in identification could be explained by object contrast values (58%) and object visual angle (6%). Conclusions. When acuity is severely limited, illumination, distance, color, height, and shape influence the identification and detection of simple 3D objects. These effects can be explained in large part by the impact of these variables on object contrast and visual angle. Basic design principles for improving object visibility are discussed. PMID:23111613

  15. Invariant object recognition based on extended fragments.

    PubMed

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

    Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called "digital embryos." Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI) of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination), and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition. PMID:22936910

  16. Object Segmentation and Ground Truth in 3D Embryonic Imaging

    PubMed Central

    Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C.

    2016-01-01

    Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets. PMID:27332860

  17. 3D X-ray tomography to evaluate volumetric objects

    NASA Astrophysics Data System (ADS)

    de Oliveira, Luís. F.; Lopes, Ricardo T.; de Jesus, Edgar F. O.; Braz, Delson

    2003-06-01

    The 3D-CT and stereological techniques are used concomitantly. The quantitative stereology yields measurements that reflects areas, volumes, lengths, rates and frequencies of the test body. Two others quantification, connectivity and anisotropy, can be used as well to complete the analysis. In this paper, it is presented the application of 3D-CT and the stereological quantification to analyze a special kind of test body: ceramic filters which have an internal structure similar to cancellous bone. The stereology is adapted to work with the 3D nature of the tomographic data. It is presented too the results of connectivity and anisotropy.

  18. 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.

  19. Reconstruction and 3D visualisation based on objective real 3D based documentation.

    PubMed

    Bolliger, Michael J; Buck, Ursula; Thali, Michael J; Bolliger, Stephan A

    2012-09-01

    Reconstructions based directly upon forensic evidence alone are called primary information. Historically this consists of documentation of findings by verbal protocols, photographs and other visual means. Currently modern imaging techniques such as 3D surface scanning and radiological methods (computer tomography, magnetic resonance imaging) are also applied. Secondary interpretation is based on facts and the examiner's experience. Usually such reconstructive expertises are given in written form, and are often enhanced by sketches. However, narrative interpretations can, especially in complex courses of action, be difficult to present and can be misunderstood. In this report we demonstrate the use of graphic reconstruction of secondary interpretation with supporting pictorial evidence, applying digital visualisation (using 'Poser') or scientific animation (using '3D Studio Max', 'Maya') and present methods of clearly distinguishing between factual documentation and examiners' interpretation based on three cases. The first case involved a pedestrian who was initially struck by a car on a motorway and was then run over by a second car. The second case involved a suicidal gunshot to the head with a rifle, in which the trigger was pushed with a rod. The third case dealt with a collision between two motorcycles. Pictorial reconstruction of the secondary interpretation of these cases has several advantages. The images enable an immediate overview, give rise to enhanced clarity, and compel the examiner to look at all details if he or she is to create a complete image. PMID:21979427

  20. A framework for the recognition of 3D faces and expressions

    NASA Astrophysics Data System (ADS)

    Li, Chao; Barreto, Armando

    2006-04-01

    Face recognition technology has been a focus both in academia and industry for the last couple of years because of its wide potential applications and its importance to meet the security needs of today's world. Most of the systems developed are based on 2D face recognition technology, which uses pictures for data processing. With the development of 3D imaging technology, 3D face recognition emerges as an alternative to overcome the difficulties inherent with 2D face recognition, i.e. sensitivity to illumination conditions and orientation positioning of the subject. But 3D face recognition still needs to tackle the problem of deformation of facial geometry that results from the expression changes of a subject. To deal with this issue, a 3D face recognition framework is proposed in this paper. It is composed of three subsystems: an expression recognition system, a system for the identification of faces with expression, and neutral face recognition system. A system for the recognition of faces with one type of expression (happiness) and neutral faces was implemented and tested on a database of 30 subjects. The results proved the feasibility of this framework.

  1. Viewpoint Invariant Gesture Recognition and 3D Hand Pose Estimation Using RGB-D

    ERIC Educational Resources Information Center

    Doliotis, Paul

    2013-01-01

    The broad application domain of the work presented in this thesis is pattern classification with a focus on gesture recognition and 3D hand pose estimation. One of the main contributions of the proposed thesis is a novel method for 3D hand pose estimation using RGB-D. Hand pose estimation is formulated as a database retrieval problem. The proposed…

  2. Learning the 3-D structure of objects from 2-D views depends on shape, not format

    PubMed Central

    Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

    2016-01-01

    Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

  3. Learning the 3-D structure of objects from 2-D views depends on shape, not format.

    PubMed

    Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

    2016-05-01

    Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

  4. 3D CARS image reconstruction and pattern recognition on SHG images

    NASA Astrophysics Data System (ADS)

    Medyukhina, Anna; Vogler, Nadine; Latka, Ines; Dietzek, Benjamin; Cicchi, Riccardo; Pavone, Francesco S.; Popp, Jürgen

    2012-06-01

    Nonlinear optical imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or second-harmonic generation (SHG) show great potential for in-vivo investigations of tissue. While the microspectroscopic imaging tools are established, automized data evaluation, i.e. image pattern recognition and automized image classification, of nonlinear optical images still bares great possibilities for future developments towards an objective clinical diagnosis. This contribution details the capability of nonlinear microscopy for both 3D visualization of human tissues and automated discrimination between healthy and diseased patterns using ex-vivo human skin samples. By means of CARS image alignment we show how to obtain a quasi-3D model of a skin biopsy, which allows us to trace the tissue structure in different projections. Furthermore, the potential of automated pattern and organization recognition to distinguish between healthy and keloidal skin tissue is discussed. A first classification algorithm employs the intrinsic geometrical features of collagen, which can be efficiently visualized by SHG microscopy. The shape of the collagen pattern allows conclusions about the physiological state of the skin, as the typical wavy collagen structure of healthy skin is disturbed e.g. in keloid formation. Based on the different collagen patterns a quantitative score characterizing the collagen waviness - and hence reflecting the physiological state of the tissue - is obtained. Further, two additional scoring methods for collagen organization, respectively based on a statistical analysis of the mutual organization of fibers and on FFT, are presented.

  5. 3D face recognition under expressions, occlusions, and pose variations.

    PubMed

    Drira, Hassen; Ben Amor, Boulbaba; Srivastava, Anuj; Daoudi, Mohamed; Slama, Rim

    2013-09-01

    We propose a novel geometric framework for analyzing 3D faces, with the specific goals of comparing, matching, and averaging their shapes. Here we represent facial surfaces by radial curves emanating from the nose tips and use elastic shape analysis of these curves to develop a Riemannian framework for analyzing shapes of full facial surfaces. This representation, along with the elastic Riemannian metric, seems natural for measuring facial deformations and is robust to challenges such as large facial expressions (especially those with open mouths), large pose variations, missing parts, and partial occlusions due to glasses, hair, and so on. This framework is shown to be promising from both--empirical and theoretical--perspectives. In terms of the empirical evaluation, our results match or improve upon the state-of-the-art methods on three prominent databases: FRGCv2, GavabDB, and Bosphorus, each posing a different type of challenge. From a theoretical perspective, this framework allows for formal statistical inferences, such as the estimation of missing facial parts using PCA on tangent spaces and computing average shapes. PMID:23868784

  6. Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition

    PubMed Central

    Ming, Yue; Wang, Guangchao; Fan, Chunxiao

    2015-01-01

    With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition. PMID:25942404

  7. Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

    PubMed

    Ming, Yue; Wang, Guangchao; Fan, Chunxiao

    2015-01-01

    With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition. PMID:25942404

  8. Real-time automated 3D sensing, detection, and recognition of dynamic biological micro-organic events

    NASA Astrophysics Data System (ADS)

    Javidi, Bahram; Yeom, Seokwon; Moon, Inkyu; Daneshpanah, Mehdi

    2006-05-01

    In this paper, we present an overview of three-dimensional (3D) optical imaging techniques for real-time automated sensing, visualization, and recognition of dynamic biological microorganisms. Real time sensing and 3D reconstruction of the dynamic biological microscopic objects can be performed by single-exposure on-line (SEOL) digital holographic microscopy. A coherent 3D microscope-based interferometer is constructed to record digital holograms of dynamic micro biological events. Complex amplitude 3D images of the biological microorganisms are computationally reconstructed at different depths by digital signal processing. Bayesian segmentation algorithms are applied to identify regions of interest for further processing. A number of pattern recognition approaches are addressed to identify and recognize the microorganisms. One uses 3D morphology of the microorganisms by analyzing 3D geometrical shapes which is composed of magnitude and phase. Segmentation, feature extraction, graph matching, feature selection, and training and decision rules are used to recognize the biological microorganisms. In a different approach, 3D technique is used that are tolerant to the varying shapes of the non-rigid biological microorganisms. After segmentation, a number of sampling patches are arbitrarily extracted from the complex amplitudes of the reconstructed 3D biological microorganism. These patches are processed using a number of cost functions and statistical inference theory for the equality of means and equality of variances between the sampling segments. Also, we discuss the possibility of employing computational integral imaging for 3D sensing, visualization, and recognition of biological microorganisms illuminated under incoherent light. Experimental results with several biological microorganisms are presented to illustrate detection, segmentation, and identification of micro biological events.

  9. 3D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation

    PubMed Central

    Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

    2014-01-01

    Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm. PMID:24940876

  10. 3D face recognition based on multiple keypoint descriptors and sparse representation.

    PubMed

    Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

    2014-01-01

    Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm. PMID:24940876

  11. Face recognition using 3D facial shape and color map information: comparison and combination

    NASA Astrophysics Data System (ADS)

    Godil, Afzal; Ressler, Sandy; Grother, Patrick

    2004-08-01

    In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information. The 3D surface and color map data are from the CAESAR anthropometric database. We find that the recognition performance is not very different between 3D surface and color map information using a principal component analysis algorithm. We also discuss the different techniques for the combination of the 3D surface and color map information for multi-modal recognition by using different fusion approaches and show that there is significant improvement in results. The effectiveness of various techniques is compared and evaluated on a dataset with 200 subjects in two different positions.

  12. Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    SciTech Connect

    Deptuch, Gregory; Hoff, Jim; Kwan, Simon; Lipton, Ron; Liu, Ted; Ramberg, Erik; Todri, Aida; Yarema, Ray; Demarteua, Marcel,; Drake, Gary; Weerts, Harry; /Argonne /Chicago U. /Padua U. /INFN, Padua

    2010-10-01

    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.

  13. Extension of RCC Topological Relations for 3d Complex Objects Components Extracted from 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Xing, Xu-Feng; Abolfazl Mostafavia, Mir; Wang, Chen

    2016-06-01

    Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.

  14. Color and size interactions in a real 3D object similarity task.

    PubMed

    Ling, Yazhu; Hurlbert, Anya

    2004-08-31

    In the natural world, objects are characterized by a variety of attributes, including color and shape. The contributions of these two attributes to object recognition are typically studied independently of each other, yet they are likely to interact in natural tasks. Here we examine whether color and size (a component of shape) interact in a real three-dimensional (3D) object similarity task, using solid domelike objects whose distinct apparent surface colors are independently controlled via spatially restricted illumination from a data projector hidden to the observer. The novel experimental setup preserves natural cues to 3D shape from shading, binocular disparity, motion parallax, and surface texture cues, while also providing the flexibility and ease of computer control. Observers performed three distinct tasks: two unimodal discrimination tasks, and an object similarity task. Depending on the task, the observer was instructed to select the indicated alternative object which was "bigger than," "the same color as," or "most similar to" the designated reference object, all of which varied in both size and color between trials. For both unimodal discrimination tasks, discrimination thresholds for the tested attribute (e.g., color) were increased by differences in the secondary attribute (e.g., size), although this effect was more robust in the color task. For the unimodal size-discrimination task, the strongest effects of the secondary attribute (color) occurred as a perceptual bias, which we call the "saturation-size effect": Objects with more saturated colors appear larger than objects with less saturated colors. In the object similarity task, discrimination thresholds for color or size differences were significantly larger than in the unimodal discrimination tasks. We conclude that color and size interact in determining object similarity, and are effectively analyzed on a coarser scale, due to noise in the similarity estimates of the individual attributes

  15. Flexible simulation strategy for modeling 3D cultural objects based on multisource remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Guienko, Guennadi; Levin, Eugene

    2003-01-01

    New ideas and solutions never come alone. Although automated feature extraction is not sufficiently mature to move from the realm of scientific investigation into the category of production technology, a new goal has arisen: 3D simulation of real-world objects, extracted from images. This task, which evolved from feature extraction and is not an easy task itself, becomes even more complex, multi-leveled, and often uncertain and fuzzy when one exploits time-sequenced multi-source remotely sensed visual data. The basic components of the process are familiar image processing tasks: fusion of various types of imagery, automatic recognition of objects, removng those objects from the source images, and replacing them in the images with their realistic simulated "twin" object rendering. This paper discusses how to aggregate the most appropriate approach to each task into one technological process in order to develop a Manipulator for Visual Simulation of 3D objects (ManVIS) that is independent or imagery/format/media. The technology could be made general by combining a number of competent special purpose algorithms under appropriate contextual, geometric, spatial, and temporal constraints derived from a-priori knowledge. This could be achieved by planning the simulation in an Open Structure Simulation Strategy Manager (O3SM) a distinct component of ManVIS building the simulation strategy before beginning actual image manipulation.

  16. Recognition Accuracy Using 3D Endoscopic Images for Superficial Gastrointestinal Cancer: A Crossover Study

    PubMed Central

    Kaise, Mitsuru; Kikuchi, Daisuke; Iizuka, Toshiro; Fukuma, Yumiko; Kuribayashi, Yasutaka; Tanaka, Masami; Toba, Takahito; Furuhata, Tsukasa; Yamashita, Satoshi; Matsui, Akira; Mitani, Toshifumi; Hoteya, Shu

    2016-01-01

    Aim. To determine whether 3D endoscopic images improved recognition accuracy for superficial gastrointestinal cancer compared with 2D images. Methods. We created an image catalog using 2D and 3D images of 20 specimens resected by endoscopic submucosal dissection. The twelve participants were allocated into two groups. Group 1 evaluated only 2D images at first, group 2 evaluated 3D images, and, after an interval of 2 weeks, group 1 next evaluated 3D and group 2 evaluated 2D images. The evaluation items were as follows: (1) diagnostic accuracy of the tumor extent and (2) confidence levels in assessing (a) tumor extent, (b) morphology, (c) microsurface structure, and (d) comprehensive recognition. Results. The use of 3D images resulted in an improvement in diagnostic accuracy in both group 1 (2D: 76.9%, 3D: 78.6%) and group 2 (2D: 79.9%, 3D: 83.6%), with no statistically significant difference. The confidence levels were higher for all items ((a) to (d)) when 3D images were used. With respect to experience, the degree of the improvement showed the following trend: novices > trainees > experts. Conclusions. By conversion into 3D images, there was a significant improvement in the diagnostic confidence level for superficial tumors, and the improvement was greater in individuals with lower endoscopic expertise. PMID:27597863

  17. Recognition Accuracy Using 3D Endoscopic Images for Superficial Gastrointestinal Cancer: A Crossover Study.

    PubMed

    Nomura, Kosuke; Kaise, Mitsuru; Kikuchi, Daisuke; Iizuka, Toshiro; Fukuma, Yumiko; Kuribayashi, Yasutaka; Tanaka, Masami; Toba, Takahito; Furuhata, Tsukasa; Yamashita, Satoshi; Matsui, Akira; Mitani, Toshifumi; Hoteya, Shu

    2016-01-01

    Aim. To determine whether 3D endoscopic images improved recognition accuracy for superficial gastrointestinal cancer compared with 2D images. Methods. We created an image catalog using 2D and 3D images of 20 specimens resected by endoscopic submucosal dissection. The twelve participants were allocated into two groups. Group 1 evaluated only 2D images at first, group 2 evaluated 3D images, and, after an interval of 2 weeks, group 1 next evaluated 3D and group 2 evaluated 2D images. The evaluation items were as follows: (1) diagnostic accuracy of the tumor extent and (2) confidence levels in assessing (a) tumor extent, (b) morphology, (c) microsurface structure, and (d) comprehensive recognition. Results. The use of 3D images resulted in an improvement in diagnostic accuracy in both group 1 (2D: 76.9%, 3D: 78.6%) and group 2 (2D: 79.9%, 3D: 83.6%), with no statistically significant difference. The confidence levels were higher for all items ((a) to (d)) when 3D images were used. With respect to experience, the degree of the improvement showed the following trend: novices > trainees > experts. Conclusions. By conversion into 3D images, there was a significant improvement in the diagnostic confidence level for superficial tumors, and the improvement was greater in individuals with lower endoscopic expertise. PMID:27597863

  18. Object-oriented urban 3D spatial data model organization method

    NASA Astrophysics Data System (ADS)

    Li, Jing-wen; Li, Wen-qing; Lv, Nan; Su, Tao

    2015-12-01

    This paper combined the 3d data model with object-oriented organization method, put forward the model of 3d data based on object-oriented method, implemented the city 3d model to quickly build logical semantic expression and model, solved the city 3d spatial information representation problem of the same location with multiple property and the same property with multiple locations, designed the space object structure of point, line, polygon, body for city of 3d spatial database, and provided a new thought and method for the city 3d GIS model and organization management.

  19. Disruptive camouflage impairs object recognition.

    PubMed

    Webster, Richard J; Hassall, Christopher; Herdman, Chris M; Godin, Jean-Guy J; Sherratt, Thomas N

    2013-01-01

    Whether hiding from predators, or avoiding battlefield casualties, camouflage is widely employed to prevent detection. Disruptive coloration is a seemingly well-known camouflage mechanism proposed to function by breaking up an object's salient features (for example their characteristic outline), rendering objects more difficult to recognize. However, while a wide range of animals are thought to evade detection using disruptive patterns, there is no direct experimental evidence that disruptive coloration impairs recognition. Using humans searching for computer-generated moth targets, we demonstrate that the number of edge-intersecting patches on a target reduces the likelihood of it being detected, even at the expense of reduced background matching. Crucially, eye-tracking data show that targets with more edge-intersecting patches were looked at for longer periods prior to attack, and passed-over more frequently during search tasks. We therefore show directly that edge patches enhance survivorship by impairing recognition, confirming that disruptive coloration is a distinct camouflage strategy, not simply an artefact of background matching. PMID:24152693

  20. Reliable Gait Recognition Using 3D Reconstructions and Random Forests - An Anthropometric Approach.

    PubMed

    Sandau, Martin; Heimbürger, Rikke V; Jensen, Karl E; Moeslund, Thomas B; Aanaes, Henrik; Alkjaer, Tine; Simonsen, Erik B

    2016-05-01

    Photogrammetric measurements of bodily dimensions and analysis of gait patterns in CCTV are important tools in forensic investigations but accurate extraction of the measurements are challenging. This study tested whether manual annotation of the joint centers on 3D reconstructions could provide reliable recognition. Sixteen participants performed normal walking where 3D reconstructions were obtained continually. Segment lengths and kinematics from the extremities were manually extracted by eight expert observers. The results showed that all the participants were recognized, assuming the same expert annotated the data. Recognition based on data annotated by different experts was less reliable achieving 72.6% correct recognitions as some parameters were heavily affected by interobserver variability. This study verified that 3D reconstructions are feasible for forensic gait analysis as an improved alternative to conventional CCTV. However, further studies are needed to account for the use of different clothing, field conditions, etc. PMID:27122399

  1. Recurrent Processing during Object Recognition

    PubMed Central

    O’Reilly, Randall C.; Wyatte, Dean; Herd, Seth; Mingus, Brian; Jilk, David J.

    2013-01-01

    How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of naturally occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain’s visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time. PMID:23554596

  2. Frio, Yegua objectives of E. Texas 3D seismic

    SciTech Connect

    1996-07-01

    Houston companies plan to explore deeper formations along the Sabine River on the Texas and Louisiana Gulf Coast. PetroGuard Co. Inc. and Jebco Seismic Inc., Houston, jointly secured a seismic and leasing option from Hankamer family et al. on about 120 sq miles in Newton County, Tex., and Calcasieu Parish, La. PetroGuard, which specializes in oilfield rehabilitation, has production experience in the area. Historic production in the area spans three major geologic trends: Oligocene Frio/Hackberry, downdip and mid-dip Eocene Yegua, and Eocene Wilcox. In the southern part of the area, to be explored first, the trends lie at 9,000--10,000 ft, 10,000--12,000 ft, and 14,000--15,000 ft, respectively. Output Exploration Co., an affiliate of Input/Output Inc., Houston, acquired from PetroGuard and Jebco all exploratory drilling rights in the option area. Output will conduct 3D seismic operations over nearly half the acreage this summer. Data acquisition started late this spring. Output plans to use a combination of a traditional land recording system and I/O`s new RSR 24 bit radio telemetry system because the area spans environments from dry land to swamp.

  3. Multi-view indoor human behavior recognition based on 3D skeleton

    NASA Astrophysics Data System (ADS)

    Peng, Ling; Lu, Tongwei; Min, Feng

    2015-12-01

    For the problems caused by viewpoint changes in activity recognition, a multi-view interior human behavior recognition method based on 3D framework is presented. First, Microsoft's Kinect device is used to obtain body motion video in the positive perspective, the oblique angle and the side perspective. Second, it extracts bone joints and get global human features and the local features of arms and legs at the same time to form 3D skeletal features set. Third, online dictionary learning on feature set is used to reduce the dimension of feature. Finally, linear support vector machine (LSVM) is used to obtain the results of behavior recognition. The experimental results show that this method has better recognition rate.

  4. Automatic anatomy recognition of sparse objects

    NASA Astrophysics Data System (ADS)

    Zhao, Liming; Udupa, Jayaram K.; Odhner, Dewey; Wang, Huiqian; Tong, Yubing; Torigian, Drew A.

    2015-03-01

    A general body-wide automatic anatomy recognition (AAR) methodology was proposed in our previous work based on hierarchical fuzzy models of multitudes of objects which was not tied to any specific organ system, body region, or image modality. That work revealed the challenges encountered in modeling, recognizing, and delineating sparse objects throughout the body (compared to their non-sparse counterparts) if the models are based on the object's exact geometric representations. The challenges stem mainly from the variation in sparse objects in their shape, topology, geographic layout, and relationship to other objects. That led to the idea of modeling sparse objects not from the precise geometric representations of their samples but by using a properly designed optimal super form. This paper presents the underlying improved methodology which includes 5 steps: (a) Collecting image data from a specific population group G and body region Β and delineating in these images the objects in Β to be modeled; (b) Building a super form, S-form, for each object O in Β; (c) Refining the S-form of O to construct an optimal (minimal) super form, S*-form, which constitutes the (fuzzy) model of O; (d) Recognizing objects in Β using the S*-form; (e) Defining confounding and background objects in each S*-form for each object and performing optimal delineation. Our evaluations based on 50 3D computed tomography (CT) image sets in the thorax on four sparse objects indicate that substantially improved performance (FPVF~2%, FNVF~10%, and success where the previous approach failed) can be achieved using the new approach.

  5. Integrating task-directed planning with reactive object recognition

    NASA Astrophysics Data System (ADS)

    Dickinson, Sven J.; Stevenson, Suzanne; Amdur, Eugene; Tsotsos, John K.; Olsson, Lars

    1993-08-01

    We describe a robot vision system that achieves complex object recognition with two layers of behaviors, performing the tasks of planning and object recognition, respectively. The recognition layer is a pipeline in which successive stages take in images from a stereo head, recover relevant features, build intermediate representations, and deposit 3-D objects into a world model. Each stage is an independent process that reacts automatically to output from the previous stage. This reactive system operates continuously and autonomously to construct the robot's 3-D model of the environment. Sitting above the recognition pipeline is the planner which is responsible for populating the world model with objects that satisfy the high-level goals of the system. For example, upon examination of the world model, the planner can decide to direct the head to another location, gating new images into the recognition pipeline, causing new objects to be deposited into the world model. Alternatively, the planner can alter the recognition behavior of the pipeline so that objects of a certain type or at a certain location appear in the world model.

  6. Relations among Early Object Recognition Skills: Objects and Letters

    ERIC Educational Resources Information Center

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

    2015-01-01

    Human visual object recognition is multifaceted and comprised of several domains of expertise. Developmental relations between young children's letter recognition and their 3-dimensional object recognition abilities are implicated on several grounds but have received little research attention. Here, we ask how preschoolers' success in recognizing…

  7. Object recognition and localization: the role of tactile sensors.

    PubMed

    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

  8. 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

  9. Knowledge Based 3d Building Model Recognition Using Convolutional Neural Networks from LIDAR and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Alidoost, F.; Arefi, H.

    2016-06-01

    In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D models of buildings as a key element of city structures for numerous applications in urban mapping. In this paper, a novel and model-based approach is proposed for automatic recognition of buildings' roof models such as flat, gable, hip, and pyramid hip roof models based on deep structures for hierarchical learning of features that are extracted from both LiDAR and aerial ortho-photos. The main steps of this approach include building segmentation, feature extraction and learning, and finally building roof labeling in a supervised pre-trained Convolutional Neural Network (CNN) framework to have an automatic recognition system for various types of buildings over an urban area. In this framework, the height information provides invariant geometric features for convolutional neural network to localize the boundary of each individual roofs. CNN is a kind of feed-forward neural network with the multilayer perceptron concept which consists of a number of convolutional and subsampling layers in an adaptable structure and it is widely used in pattern recognition and object detection application. Since the training dataset is a small library of labeled models for different shapes of roofs, the computation time of learning can be decreased significantly using the pre-trained models. The experimental results highlight the effectiveness of the deep learning approach to detect and extract the pattern of buildings' roofs automatically considering the complementary nature of height and RGB information.

  10. The impact of specular highlights on 3D-2D face recognition

    NASA Astrophysics Data System (ADS)

    Christlein, Vincent; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis

    2013-05-01

    One of the most popular form of biometrics is face recognition. Face recognition techniques typically assume that a face exhibits Lambertian reectance. However, a face often exhibits prominent specularities, especially in outdoor environments. These specular highlights can compromise an identity authentication. In this work, we analyze the impact of such highlights on a 3D-2D face recognition system. First, we investigate three different specularity removal methods as preprocessing steps for face recognition. Then, we explicitly model facial specularities within the face detection system with the Cook-Torrance reflectance model. In our experiments, specularity removal increases the recognition rate on an outdoor face database by about 5% at a false alarm rate of 10-3. The integration of the Cook-Torrance model further improves these results, increasing the verification rate by 19% at a FAR of 10-3.

  11. Learning deformation model for expression-robust 3D face recognition

    NASA Astrophysics Data System (ADS)

    Guo, Zhe; Liu, Shu; Wang, Yi; Lei, Tao

    2015-12-01

    Expression change is the major cause of local plastic deformation of the facial surface. The intra-class differences with large expression change somehow are larger than the inter-class differences as it's difficult to distinguish the same individual with facial expression change. In this paper, an expression-robust 3D face recognition method is proposed by learning expression deformation model. The expression of the individuals on the training set is modeled by principal component analysis, the main components are retained to construct the facial deformation model. For the test 3D face, the shape difference between the test and the neutral face in training set is used for reconstructing the expression change by the constructed deformation model. The reconstruction residual error is used for face recognition. The average recognition rate on GavabDB and self-built database reaches 85.1% and 83%, respectively, which shows strong robustness for expression changes.

  12. Reducing Non-Uniqueness in Satellite Gravity Inversion using 3D Object Oriented Image Analysis Techniques

    NASA Astrophysics Data System (ADS)

    Fadel, I.; van der Meijde, M.; Kerle, N.

    2013-12-01

    Non-uniqueness of satellite gravity interpretation has been usually reduced by using a priori information from various sources, e.g. seismic tomography models. The reduction in non-uniqueness has been based on velocity-density conversion formulas or user interpretation for 3D subsurface structures (objects) in seismic tomography models. However, these processes introduce additional uncertainty through the conversion relations due to the dependency on the other physical parameters such as temperature and pressure, or through the bias in the interpretation due to user choices and experience. In this research, a new methodology is introduced to extract the 3D subsurface structures from 3D geophysical data using a state-of-art 3D Object Oriented Image Analysis (OOA) technique. 3D OOA is tested using a set of synthetic models that simulate the real situation in the study area of this research. Then, 3D OOA is used to extract 3D subsurface objects from a real 3D seismic tomography model. The extracted 3D objects are used to reconstruct a forward model and its response is compared with the measured satellite gravity. Finally, the result of the forward modelling, based on the extracted 3D objects, is used to constrain the inversion process of satellite gravity data. Through this work, a new object-based approach is introduced to interpret and extract the 3D subsurface objects from 3D geophysical data. This can be used to constrain modelling and inversion of potential field data using the extracted 3D subsurface structures from other methods. In summary, a new approach is introduced to constrain inversion of satellite gravity measurements and enhance interpretation capabilities.

  13. 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

  14. 3D imaging of amplitude objects embedded in phase objects using transport of intensity

    NASA Astrophysics Data System (ADS)

    Banerjee, Partha; Basunia, Mahmudunnabi

    2015-09-01

    The amplitude and phase of the complex optical field in the Helmholtz equation obey a pair of coupled equations, arising from equating the real and imaginary parts. The imaginary part yields the transport of intensity equation (TIE), which can be used to derive the phase distribution at the observation plane. If a phase object is approximately imaged on the recording plane(s), TIE yields the phase without the need for phase unwrapping. In our experiment, the 3D image of a phase object and an amplitude object embedded in a phase object is recovered. The phase object is created by heating a liquid, comprising a solution of red dye in alcohol, using a focused 514 nm laser beam to the point where self-phase modulation of the beam is observed. The optical intensities are recorded at various planes during propagation of a low power 633 nm laser beam through the liquid. In the process of applying TIE to derive the phase at the observation plane, the real part of the complex equation is also examined as a cross-check of our calculations. For pure phase objects, it is shown that the real part of the complex equation is best satisfied around the image plane. Alternatively, it is proposed that this information can be used to determine the optimum image plane.

  15. An object-oriented 3D integral data model for digital city and digital mine

    NASA Astrophysics Data System (ADS)

    Wu, Lixin; Wang, Yanbing; Che, Defu; Xu, Lei; Chen, Xuexi; Jiang, Yun; Shi, Wenzhong

    2005-10-01

    With the rapid development of urban, city space extended from surface to subsurface. As the important data source for the representation of city spatial information, 3D city spatial data have the characteristics of multi-object, heterogeneity and multi-structure. It could be classified referring to the geo-surface into three kinds: above-surface data, surface data and subsurface data. The current research on 3D city spatial information system is divided naturally into two different branch, 3D City GIS (3D CGIS) and 3D Geological Modeling (3DGM). The former emphasizes on the 3D visualization of buildings and the terrain of city, while the latter emphasizes on the visualization of geological bodies and structures. Although, it is extremely important for city planning and construction to integrate all the city spatial information including above-surface, surface and subsurface objects to conduct integral analysis and spatial manipulation. However, either 3D CGIS or 3DGM is currently difficult to realize the information integration, integral analysis and spatial manipulation. Considering 3D spatial modeling theory and methodologies, an object-oriented 3D integral spatial data model (OO3D-ISDM) is presented and software realized. The model integrates geographical objects, surface buildings and geological objects together seamlessly with TIN being its coupling interface. This paper introduced the conceptual model of OO3D-ISDM, which is comprised of 4 spatial elements, i.e. point, line, face and body, and 4 geometric primitives, i.e. vertex, segment, triangle and generalized tri-prism (GTP). The spatial model represents the geometry of surface buildings and geographical objects with triangles, and geological objects with GTP. Any of the represented objects, no mater surface buildings, terrain or subsurface objects, could be described with the basic geometry element, i.e. triangle. So the 3D spatial objects, surface buildings, terrain and geological objects can be

  16. A new method of 3D scene recognition from still images

    NASA Astrophysics Data System (ADS)

    Zheng, Li-ming; Wang, Xing-song

    2014-04-01

    Most methods of monocular visual three dimensional (3D) scene recognition involve supervised machine learning. However, these methods often rely on prior knowledge. Specifically, they learn the image scene as part of a training dataset. For this reason, when the sampling equipment or scene is changed, monocular visual 3D scene recognition may fail. To cope with this problem, a new method of unsupervised learning for monocular visual 3D scene recognition is here proposed. First, the image is made using superpixel segmentation based on the CIELAB color space values L, a, and b and on the coordinate values x and y of pixels, forming a superpixel image with a specific density. Second, a spectral clustering algorithm based on the superpixels' color characteristics and neighboring relationships was used to reduce the dimensions of the superpixel image. Third, the fuzzy distribution density functions representing sky, ground, and façade are multiplied with the segment pixels, where the expectations of these segments are obtained. A preliminary classification of sky, ground, and façade is generated in this way. Fourth, the most accurate classification images of sky, ground, and façade were extracted through the tier-1 wavelet sampling and Manhattan direction feature. Finally, a depth perception map is generated based on the pinhole imaging model and the linear perspective information of ground surface. Here, 400 images of Make3D Image data from the Cornell University website were used to test the algorithm. The experimental results showed that this unsupervised learning method provides a more effective monocular visual 3D scene recognition model than other methods.

  17. 3-D Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold.

    PubMed

    Devanne, Maxime; Wannous, Hazem; Berretti, Stefano; Pala, Pietro; Daoudi, Mohamed; Del Bimbo, Alberto

    2015-07-01

    Recognizing human actions in 3-D video sequences is an important open problem that is currently at the heart of many research domains including surveillance, natural interfaces and rehabilitation. However, the design and development of models for action recognition that are both accurate and efficient is a challenging task due to the variability of the human pose, clothing and appearance. In this paper, we propose a new framework to extract a compact representation of a human action captured through a depth sensor, and enable accurate action recognition. The proposed solution develops on fitting a human skeleton model to acquired data so as to represent the 3-D coordinates of the joints and their change over time as a trajectory in a suitable action space. Thanks to such a 3-D joint-based framework, the proposed solution is capable to capture both the shape and the dynamics of the human body, simultaneously. The action recognition problem is then formulated as the problem of computing the similarity between the shape of trajectories in a Riemannian manifold. Classification using k-nearest neighbors is finally performed on this manifold taking advantage of Riemannian geometry in the open curve shape space. Experiments are carried out on four representative benchmarks to demonstrate the potential of the proposed solution in terms of accuracy/latency for a low-latency action recognition. Comparative results with state-of-the-art methods are reported. PMID:25216492

  18. Whole versus Part Presentations of the Interactive 3D Graphics Learning Objects

    ERIC Educational Resources Information Center

    Azmy, Nabil Gad; Ismaeel, Dina Ahmed

    2010-01-01

    The purpose of this study is to present an analysis of how the structure and design of the Interactive 3D Graphics Learning Objects can be effective and efficient in terms of Performance, Time on task, and Learning Efficiency. The study explored two treatments, namely whole versus Part Presentations of the Interactive 3D Graphics Learning Objects,…

  19. Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

    NASA Astrophysics Data System (ADS)

    Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

    2016-06-01

    High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

  20. 3D object-oriented image analysis in 3D geophysical modelling: Analysing the central part of the East African Rift System

    NASA Astrophysics Data System (ADS)

    Fadel, I.; van der Meijde, M.; Kerle, N.; Lauritsen, N.

    2015-03-01

    Non-uniqueness of satellite gravity interpretation has traditionally been reduced by using a priori information from seismic tomography models. This reduction in the non-uniqueness has been based on velocity-density conversion formulas or user interpretation of the 3D subsurface structures (objects) based on the seismic tomography models and then forward modelling these objects. However, this form of object-based approach has been done without a standardized methodology on how to extract the subsurface structures from the 3D models. In this research, a 3D object-oriented image analysis (3D OOA) approach was implemented to extract the 3D subsurface structures from geophysical data. The approach was applied on a 3D shear wave seismic tomography model of the central part of the East African Rift System. Subsequently, the extracted 3D objects from the tomography model were reconstructed in the 3D interactive modelling environment IGMAS+, and their density contrast values were calculated using an object-based inversion technique to calculate the forward signal of the objects and compare it with the measured satellite gravity. Thus, a new object-based approach was implemented to interpret and extract the 3D subsurface objects from 3D geophysical data. We also introduce a new approach to constrain the interpretation of the satellite gravity measurements that can be applied using any 3D geophysical model.

  1. 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

  2. An Overview of 3d Topology for Ladm-Based Objects

    NASA Astrophysics Data System (ADS)

    Zulkifli, N. A.; Rahman, A. A.; van Oosterom, P.

    2015-10-01

    This paper reviews 3D topology within Land Administration Domain Model (LADM) international standard. It is important to review characteristic of the different 3D topological models and to choose the most suitable model for certain applications. The characteristic of the different 3D topological models are based on several main aspects (e.g. space or plane partition, used primitives, constructive rules, orientation and explicit or implicit relationships). The most suitable 3D topological model depends on the type of application it is used for. There is no single 3D topology model best suitable for all types of applications. Therefore, it is very important to define the requirements of the 3D topology model. The context of this paper is a 3D topology for LADM-based objects.

  3. 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.

  4. Relations among early object recognition skills: Objects and letters

    PubMed Central

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

    2014-01-01

    Human visual object recognition is multifaceted, with several domains of expertise. Developmental relations between young children's letter recognition and their 3-dimensional object recognition abilities are implicated on several grounds but have received little research attention. Here, we ask how preschoolers’ success in recognizing letters relates to their ability to recognize 3-dimensional objects from sparse shape information alone. A relation is predicted because perception of the spatial relations is critical in both domains. Seventy-three 2 ½- to 4-year-old children completed a Letter Recognition task, measuring the ability to identify a named letter among 3 letters with similar shapes, and a “Shape Caricature Recognition” task, measuring recognition of familiar objects from sparse, abstract information about their part shapes and the spatial relations among those parts. Children also completed a control “Shape Bias” task, in which success depends on recognition of overall object shape but not of relational structure. Children's success in letter recognition was positively related to their shape caricature recognition scores, but not to their shape bias scores. The results suggest that letter recognition builds upon developing skills in attending to and representing the relational structure of object shape, and that these skills are common to both 2-dimensional and 3-dimensional object perception. PMID:25969673

  5. 3D Imaging for hand gesture recognition: Exploring the software-hardware interaction of current technologies

    NASA Astrophysics Data System (ADS)

    Periverzov, Frol; Ilieş, Horea T.

    2012-09-01

    Interaction with 3D information is one of the fundamental and most familiar tasks in virtually all areas of engineering and science. Several recent technological advances pave the way for developing hand gesture recognition capabilities available to all, which will lead to more intuitive and efficient 3D user interfaces (3DUI). These developments can unlock new levels of expression and productivity in all activities concerned with the creation and manipulation of virtual 3D shapes and, specifically, in engineering design. Building fully automated systems for tracking and interpreting hand gestures requires robust and efficient 3D imaging techniques as well as potent shape classifiers. We survey and explore current and emerging 3D imaging technologies, and focus, in particular, on those that can be used to build interfaces between the users' hands and the machine. The purpose of this paper is to categorize and highlight the relevant differences between these existing 3D imaging approaches in terms of the nature of the information provided, output data format, as well as the specific conditions under which these approaches yield reliable data. Furthermore we explore the impact of each of these approaches on the computational cost and reliability of the required image processing algorithms. Finally we highlight the main challenges and opportunities in developing natural user interfaces based on hand gestures, and conclude with some promising directions for future research. [Figure not available: see fulltext.

  6. 3D face recognition based on the hierarchical score-level fusion classifiers

    NASA Astrophysics Data System (ADS)

    Mráček, Štěpán.; Váša, Jan; Lankašová, Karolína; Drahanský, Martin; Doležel, Michal

    2014-05-01

    This paper describes the 3D face recognition algorithm that is based on the hierarchical score-level fusion clas-sifiers. In a simple (unimodal) biometric pipeline, the feature vector is extracted from the input data and subsequently compared with the template stored in the database. In our approachm, we utilize several feature extraction algorithms. We use 6 different image representations of the input 3D face data. Moreover, we are using Gabor and Gauss-Laguerre filter banks applied on the input image data that yield to 12 resulting feature vectors. Each representation is compared with corresponding counterpart from the biometric database. We also add the recognition based on the iso-geodesic curves. The final score-level fusion is performed on 13 comparison scores using the Support Vector Machine (SVM) classifier.

  7. Interactive and Stereoscopic Hybrid 3D Viewer of Radar Data with Gesture Recognition

    NASA Astrophysics Data System (ADS)

    Goenetxea, Jon; Moreno, Aitor; Unzueta, Luis; Galdós, Andoni; Segura, Álvaro

    This work presents an interactive and stereoscopic 3D viewer of weather information coming from a Doppler radar. The hybrid system shows a GIS model of the regional zone where the radar is located and the corresponding reconstructed 3D volume weather data. To enhance the immersiveness of the navigation, stereoscopic visualization has been added to the viewer, using a polarized glasses based system. The user can interact with the 3D virtual world using a Nintendo Wiimote for navigating through it and a Nintendo Wii Nunchuk for giving commands by means of hand gestures. We also present a dynamic gesture recognition procedure that measures the temporal advance of the performed gesture postures. Experimental results show how dynamic gestures are effectively recognized so that a more natural interaction and immersive navigation in the virtual world is achieved.

  8. Temporal-spatial modeling of fast-moving and deforming 3D objects

    NASA Astrophysics Data System (ADS)

    Wu, Xiaoliang; Wei, Youzhi

    1998-09-01

    This paper gives a brief description of the method and techniques developed for the modeling and reconstruction of fast moving and deforming 3D objects. A new approach using close-range digital terrestrial photogrammetry in conjunction with high speed photography and videography is proposed. A sequential image matching method (SIM) has been developed to automatically process pairs of images taken continuously of any fast moving and deforming 3D objects. Using the SIM technique a temporal-spatial model (TSM) of any fast moving and deforming 3D objects can be developed. The TSM would include a series of reconstructed surface models of the fast moving and deforming 3D object in the form of 3D images. The TSM allows the 3D objects to be visualized and analyzed in sequence. The SIM method, specifically the left-right matching and forward-back matching techniques are presented in the paper. An example is given which deals with the monitoring of a typical blast rock bench in a major open pit mine in Australia. With the SIM approach and the TSM model it is possible to automatically and efficiently reconstruct the 3D images of the blasting process. This reconstruction would otherwise be impossible to achieve using a labor intensive manual processing approach based on 2D images taken from conventional high speed cameras. The case study demonstrates the potential of the SIM approach and the TSM for the automatic identification, tracking and reconstruction of any fast moving and deforming 3D targets.

  9. 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.

  10. 3D shape measurements for non-diffusive objects using fringe projection techniques

    NASA Astrophysics Data System (ADS)

    Su, Wei-Hung; Tseng, Bae-Heng; Cheng, Nai-Jen

    2013-09-01

    A scanning approach using holographic techniques to perform the 3D shape measurement for a non-diffusive object is proposed. Even though the depth discontinuity on the inspected surface is pretty high, the proposed method can retrieve the 3D shape precisely.

  11. Visual Short-Term Memory Benefit for Objects on Different 3-D Surfaces

    ERIC Educational Resources Information Center

    Xu, Yaoda; Nakayama, Ken

    2007-01-01

    Visual short-term memory (VSTM) plays an important role in visual cognition. Although objects are located on different 3-dimensional (3-D) surfaces in the real world, how VSTM capacity may be influenced by the presence of multiple 3-D surfaces has never been examined. By manipulating binocular disparities of visual displays, the authors found that…

  12. GestAction3D: A Platform for Studying Displacements and Deformations of 3D Objects Using Hands

    NASA Astrophysics Data System (ADS)

    Lingrand, Diane; Renevier, Philippe; Pinna-Déry, Anne-Marie; Cremaschi, Xavier; Lion, Stevens; Rouel, Jean-Guilhem; Jeanne, David; Cuisinaud, Philippe; Soula*, Julien

    We present a low-cost hand-based device coupled with a 3D motion recovery engine and 3D visualization. This platform aims at studying ergonomic 3D interactions in order to manipulate and deform 3D models by interacting with hands on 3D meshes. Deformations are done using different modes of interaction that we will detail in the paper. Finger extremities are attached to vertices, edges or facets. Switching from one mode to another or changing the point of view is done using gestures. The determination of the more adequate gestures is part of the work

  13. Electro-holography display using computer generated hologram of 3D objects based on projection spectra

    NASA Astrophysics Data System (ADS)

    Huang, Sujuan; Wang, Duocheng; He, Chao

    2012-11-01

    A new method of synthesizing computer-generated hologram of three-dimensional (3D) objects is proposed from their projection images. A series of projection images of 3D objects are recorded with one-dimensional azimuth scanning. According to the principles of paraboloid of revolution in 3D Fourier space and 3D central slice theorem, spectra information of 3D objects can be gathered from their projection images. Considering quantization error of horizontal and vertical directions, the spectrum information from each projection image is efficiently extracted in double circle and four circles shape, to enhance the utilization of projection spectra. Then spectra information of 3D objects from all projection images is encoded into computer-generated hologram based on Fourier transform using conjugate-symmetric extension. The hologram includes 3D information of objects. Experimental results for numerical reconstruction of the CGH at different distance validate the proposed methods and show its good performance. Electro-holographic reconstruction can be realized by using an electronic addressing reflective liquid-crystal display (LCD) spatial light modulator. The CGH from the computer is loaded onto the LCD. By illuminating a reference light from a laser source to the LCD, the amplitude and phase information included in the CGH will be reconstructed due to the diffraction of the light modulated by the LCD.

  14. Occluded human recognition for a leader following system using 3D range and image data in forest environment

    NASA Astrophysics Data System (ADS)

    Cho, Kuk; Ilyas, Muhammad; Baeg, Seung-Ho; Park, Sangdeok

    2014-06-01

    This paper describes the occluded target recognition and tracking method for a leader-following system by fusing 3D range and image data acquired from 3D light detection and ranging (LIDAR) and a color camera installed on an autonomous vehicle in forest environment. During 3D data processing, the distance-based clustering method has an instinctive problem in close encounters. In the tracking phase, we divide an object tracking process into three phases based on occlusion scenario; before an occlusion (BO) phase, a partially or fully occlusion phase and after an occlusion (AO) phase. To improve the data association performance, we use camera's rich information to find correspondence among objects during above mentioned three phases of occlusion. In this paper, we solve a correspondence problem using the color features of human objects with the sum of squared distance (SSD) and the normalized cross correlation (NCC). The features are integrated with derived windows from Harris corner. The experimental results for a leader following on an autonomous vehicle are shown with LIDAR and camera for improving a data association problem in a multiple object tracking system.

  15. 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…

  16. The Role of Object Recognition in Young Infants' Object Segregation.

    ERIC Educational Resources Information Center

    Carey, Susan; Williams, Travis

    2001-01-01

    Discusses Needham's findings by asserting that they extend understanding of infant perception by showing that the memory representations infants draw upon have bound together information about shape, color, and pattern. Considers the distinction between two senses of "recognition" and asks in which sense object recognition contributes to object…

  17. An efficient multimodal 2D-3D hybrid approach to automatic face recognition.

    PubMed

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

    2007-11-01

    We present a fully automatic face recognition algorithm and demonstrate its performance on the FRGC v2.0 data. Our algorithm is multimodal (2D and 3D) and performs hybrid (feature-based and holistic) matching in order to achieve efficiency and robustness to facial expressions. The pose of a 3D face along with its texture is automatically corrected using a novel approach based on a single automatically detected point and the Hotelling transform. A novel 3D Spherical Face Representation (SFR) is used in conjunction with the SIFT descriptor to form a rejection classifier which quickly eliminates a large number of candidate faces at an early stage for efficient recognition in case of large galleries. The remaining faces are then verified using a novel region-based matching approach which is robust to facial expressions. This approach automatically segments the eyes-forehead and the nose regions, which are relatively less sensitive to expressions, and matches them separately using a modified ICP algorithm. The results of all the matching engines are fused at the metric level to achieve higher accuracy. We use the FRGC benchmark to compare our results to other algorithms which used the same database. Our multimodal hybrid algorithm performed better than others by achieving 99.74% and 98.31% verification rates at 0.001 FAR and identification rates of 99.02% and 95.37% for probes with neutral and non-neutral expression respectively. PMID:17848775

  18. Rule-Based Orientation Recognition Of A Moving Object

    NASA Astrophysics Data System (ADS)

    Gove, Robert J.

    1989-03-01

    This paper presents a detailed description and a comparative analysis of the algorithms used to determine the position and orientation of an object in real-time. The exemplary object, a freely moving gold-fish in an aquarium, provides "real-world" motion, with definable characteristics of motion (the fish never swims upside-down) and the complexities of a non-rigid body. For simplicity of implementation, and since a restricted and stationary viewing domain exists (fish-tank), we reduced the problem of obtaining 3D correspondence information to trivial alignment calculations by using two cameras orthogonally viewing the object. We applied symbolic processing techniques to recognize the 3-D orientation of a moving object of known identity in real-time. Assuming motion, each new frame (sensed by the two cameras) provides images of the object's profile which has most likely undergone translation, rotation, scaling and/or bending of the non-rigid object since the previous frame. We developed an expert system which uses heuristics of the object's motion behavior in the form of rules and information obtained via low-level image processing (like numerical inertial axis calculations) to dynamically estimate the object's orientation. An inference engine provides these estimates at frame rates of up to 10 per second (which is essentially real-time). The advantages of the rule-based approach to orientation recognition will be compared other pattern recognition techniques. Our results of an investigation of statistical pattern recognition, neural networks, and procedural techniques for orientation recognition will be included. We implemented the algorithms in a rapid-prototyping environment, the TI-Ezplorer, equipped with an Odyssey and custom imaging hardware. A brief overview of the workstation is included to clarify one motivation for our choice of algorithms. These algorithms exploit two facets of the prototype image processing and understanding workstation - both low

  19. Representing 3D virtual objects: interaction between visuo-spatial ability and type of exploration.

    PubMed

    Meijer, Frank; van den Broek, Egon L

    2010-03-17

    We investigated individual differences in interactively exploring 3D virtual objects. 36 participants explored 24 simple and 24 difficult objects (composed of respectively three and five Biederman geons) actively, passively, or not at all. Both their 3D mental representation of the objects and visuo-spatial ability was assessed. Results show that, regardless of the object's complexity, people with a low VSA benefit from active exploration of objects, where people with a middle or high VSA do not. These findings extend and refine earlier research on interactively learning visuo-spatial information and underline the importance to take individual differences into account. PMID:20116394

  20. 3D facial expression recognition using maximum relevance minimum redundancy geometrical features

    NASA Astrophysics Data System (ADS)

    Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

    2012-12-01

    In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

  1. Dialog-Based 3D-Image Recognition Using a Domain Ontology

    NASA Astrophysics Data System (ADS)

    Hois, Joana; Wünstel, Michael; Bateman, John A.; Röfer, Thomas

    The combination of vision and speech, together with the resulting necessity for formal representations, builds a central component of an autonomous system. A robot that is supposed to navigate autonomously through space must be able to perceive its environment as automatically as possible. But each recognition system has its own inherent limits. Especially a robot whose task is to navigate through unknown terrain has to deal with unidentified or even unknown objects, thus compounding the recognition problem still further. The system described in this paper takes this into account by trying to identify objects based on their functionality where possible. To handle cases where recognition is insufficient, we examine here two further strategies: on the one hand, the linguistic reference and labeling of the unidentified objects and, on the other hand, ontological deduction. This approach then connects the probabilistic area of object recognition with the logical area of formal reasoning. In order to support formal reasoning, additional relational scene information has to be supplied by the recognition system. Moreover, for a sound ontological basis for these reasoning tasks, it is necessary to define a domain ontology that provides for the representation of real-world objects and their corresponding spatial relations in linguistic and physical respects. Physical spatial relations and objects are measured by the visual system, whereas linguistic spatial relations and objects are required for interactions with a user.

  2. Development of goniophotometric imaging system for recording reflectance spectra of 3D objects

    NASA Astrophysics Data System (ADS)

    Tonsho, Kazutaka; Akao, Y.; Tsumura, Norimichi; Miyake, Yoichi

    2001-12-01

    In recent years, it is required to develop a system for 3D capture of archives in museums and galleries. In visualizing of 3D object, it is important to reproduce both color and glossiness accurately. Our final goal is to construct digital archival systems in museum and internet or virtual museum via World Wide Web. To achieve our goal, we have developed gonio-photometric imaging system by using high accurate multi-spectral camera and 3D digitizer. In this paper, gonio-photometric imaging method is introduced for recording 3D object. 5-bands images of the object are taken under 7 different illuminants angles. The 5-band image sequences are then analyzed on the basis of both dichromatic reflection model and Phong model to extract gonio-photometric property of the object. The images of the 3D object under illuminants with arbitrary spectral radiant distribution, illuminating angles, and visual points are rendered by using OpenGL with the 3D shape and gonio-photometric property.

  3. Template protection and its implementation in 3D face recognition systems

    NASA Astrophysics Data System (ADS)

    Zhou, Xuebing

    2007-04-01

    As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

  4. Computing 3-D structure of rigid objects using stereo and motion

    NASA Technical Reports Server (NTRS)

    Nguyen, Thinh V.

    1987-01-01

    Work performed as a step toward an intelligent automatic machine vision system for 3-D imaging is discussed. The problem considered is the quantitative 3-D reconstruction of rigid objects. Motion and stereo are the two clues considered in this system. The system basically consists of three processes: the low level process to extract image features, the middle level process to establish the correspondence in the stereo (spatial) and motion (temporal) modalities, and the high level process to compute the 3-D coordinates of the corner points by integrating the spatial and temporal correspondences.

  5. 3D photography in the objective analysis of volume augmentation including fat augmentation and dermal fillers.

    PubMed

    Meier, Jason D; Glasgold, Robert A; Glasgold, Mark J

    2011-11-01

    The authors present quantitative and objective 3D data from their studies showing long-term results with facial volume augmentation. The first study analyzes fat grafting of the midface and the second study presents augmentation of the tear trough with hyaluronic filler. Surgeons using 3D quantitative analysis can learn the duration of results and the optimal amount to inject, as well as showing patients results that are not demonstrable with standard, 2D photography. PMID:22004863

  6. 2D virtual texture on 3D real object with coded structured light

    NASA Astrophysics Data System (ADS)

    Molinier, Thierry; Fofi, David; Salvi, Joaquim; Gorria, Patrick

    2008-02-01

    Augmented reality is used to improve color segmentation on human body or on precious no touch artifacts. We propose a technique to project a synthesized texture on real object without contact. Our technique can be used in medical or archaeological application. By projecting a suitable set of light patterns onto the surface of a 3D real object and by capturing images with a camera, a large number of correspondences can be found and the 3D points can be reconstructed. We aim to determine these points of correspondence between cameras and projector from a scene without explicit points and normals. We then project an adjusted texture onto the real object surface. We propose a global and automatic method to virtually texture a 3D real object.

  7. Bayesian multi-target tracking and sequential object recognition

    NASA Astrophysics Data System (ADS)

    Armbruster, Walter

    2008-04-01

    The paper considers the following problem: given a 3D model of a reference target and a sequence of images of a 3D scene, identify the object in the scene most likely to be the reference target and determine its current pose. Finding the best match in each frame independently of previous decisions is not optimal, since past information is ignored. Our solution concept uses a novel Bayesian framework for multi target tracking and object recognition to define and sequentially update the probability that the reference target is any one of the tracked objects. The approach is applied to problems of automatic lock-on and missile guidance using a laser radar seeker. Field trials have resulted in high target hit probabilities despite low resolution imagery and temporarily highly occluded targets.

  8. Gonio photometric imaging for recording of reflectance spectra of 3D objects

    NASA Astrophysics Data System (ADS)

    Miyake, Yoichi; Tsumura, Norimichi; Haneishi, Hideaki; Hayashi, Junichiro

    2002-06-01

    In recent years, it is required to develop a system for 3D capture of archives in museums and galleries. In visualizing of 3D object, it is important to reproduce both color and glossiness accurately. Our final goal is to construct digital archival systems in museum and Internet or virtual museum via World Wide Web. To archive our goal, we have developed the multi-spectral imaging systems to record and estimate reflectance spectra of the art paints based on principal component analysis and Wiener estimation method. In this paper, Gonio photometric imaging method is introduced for recording of 3D object. Five-band images of the object are taken under seven different illuminants angles. The set of five-band images are then analyzed on the basis of both dichromatic reflection model and Phong model to extract Gonio photometric information of the object. Prediction of reproduced images of the object under several illuminants and illumination angles is demonstrated and images that are synthesized with 3D wire frame image taken by 3D digitizer are also presented.

  9. A prescreener for 3D face recognition using radial symmerty and the Hausdorff fraction.

    SciTech Connect

    Koudelka, Melissa L.; Koch, Mark William; Russ, Trina Denise

    2005-04-01

    Face recognition systems require the ability to efficiently scan an existing database of faces to locate a match for a newly acquired face. The large number of faces in real world databases makes computationally intensive algorithms impractical for scanning entire databases. We propose the use of more efficient algorithms to 'prescreen' face databases, determining a limited set of likely matches that can be processed further to identify a match. We use both radial symmetry and shape to extract five features of interest on 3D range images of faces. These facial features determine a very small subset of discriminating points which serve as input to a prescreening algorithm based on a Hausdorff fraction. We show how to compute the Haudorff fraction in linear O(n) time using a range image representation. Our feature extraction and prescreening algorithms are verified using the FRGC v1.0 3D face scan data. Results show 97% of the extracted facial features are within 10 mm or less of manually marked ground truth, and the prescreener has a rank 6 recognition rate of 100%.

  10. Computer generated holograms of 3D objects with reduced number of projections

    NASA Astrophysics Data System (ADS)

    Huang, Su-juan; Liu, Dao-jin; Zhao, Jing-jing

    2010-11-01

    A new method for synthesizing computer-generated holograms of 3D objects has been proposed with reduced number of projections. According to the principles of paraboloid of revolution in 3D Fourier space, spectra information of 3D objects is gathered from projection images. We record a series of real projection images of 3D objects under incoherent white-light illumination by circular scanning method, and synthesize interpolated projection images by motion estimation and compensation between adjacent real projection images, then extract the spectra information of the 3D objects from all projection images in circle form. Because of quantization error, information extraction in two circles form is better than in single circle. Finally hologram is encoded based on computer-generated holography using a conjugate-symmetric extension. Our method significantly reduces the number of required real projections without increasing much of the computing time of the hologram and degrading the reconstructed image. Numerical reconstruction of the hologram shows good results.

  11. Generation of geometric representations of 3D objects in CAD/CAM by digital photogrammetry

    NASA Astrophysics Data System (ADS)

    Li, Rongxing

    This paper presents a method for the generation of geometric representations of 3D objects by digital photogrammetry. In CAD/CAM systems geometric modelers are usually used to create three-dimensional (3D) geometric representations for design and manufacturing purposes. However, in cases where geometric information such as dimensions and shapes of objects are not available, measurements of physically existing objects become necessary. In this paper, geometric parameters of primitives of 3D geometric representations such as Boundary Representation (B-rep), Constructive Solid Geometry (CSG), and digital surface models are determined by digital image matching techniques. An algorithm for reconstruction of surfaces with discontinuities is developed. Interfaces between digital photogrammetric data and these geometric representations are realized. This method can be applied to design and manufacturing in mechanical engineering, automobile industry, robot technology, spatial information systems and others.

  12. Effects of active navigation on object recognition in virtual environments.

    PubMed

    Hahm, Jinsun; Lee, Kanghee; Lim, Seung-Lark; Kim, Sei-Young; Kim, Hyun-Taek; Lee, Jang-Han

    2007-04-01

    We investigated the importance and efficiency of active and passive exploration on the recognition of objects in a variety of virtual environments (VEs). In this study, 54 participants were randomly allocated into one of active and passive navigation conditions. Active navigation was performed by allowing participants to self-pace and control their own navigation, but passive navigation was conducted by forced navigation. After navigating VEs, participants were asked to recognize the objects that had been in the VEs. Active navigation condition had a significantly higher percentage of hit responses (t (52) = 4.000, p < 0.01), and a significantly lower percentage of miss responses (t (52) = -3.763, p < 0.01) in object recognition than the passive condition. These results suggest that active navigation plays an important role in spatial cognition as well as providing an explanation for the efficiency of learning in a 3D-based program. PMID:17474852

  13. High-purity 3D nano-objects grown by focused-electron-beam induced deposition

    NASA Astrophysics Data System (ADS)

    Córdoba, Rosa; Sharma, Nidhi; Kölling, Sebastian; Koenraad, Paul M.; Koopmans, Bert

    2016-09-01

    To increase the efficiency of current electronics, a specific challenge for the next generation of memory, sensing and logic devices is to find suitable strategies to move from two- to three-dimensional (3D) architectures. However, the creation of real 3D nano-objects is not trivial. Emerging non-conventional nanofabrication tools are required for this purpose. One attractive method is focused-electron-beam induced deposition (FEBID), a direct-write process of 3D nano-objects. Here, we grow 3D iron and cobalt nanopillars by FEBID using diiron nonacarbonyl Fe2(CO)9, and dicobalt octacarbonyl Co2(CO)8, respectively, as starting materials. In addition, we systematically study the composition of these nanopillars at the sub-nanometer scale by atom probe tomography, explicitly mapping the homogeneity of the radial and longitudinal composition distributions. We show a way of fabricating high-purity 3D vertical nanostructures of ∼50 nm in diameter and a few micrometers in length. Our results suggest that the purity of such 3D nanoelements (above 90 at% Fe and above 95 at% Co) is directly linked to their growth regime, in which the selected deposition conditions are crucial for the final quality of the nanostructure. Moreover, we demonstrate that FEBID and the proposed characterization technique not only allow for growth and chemical analysis of single-element structures, but also offers a new way to directly study 3D core–shell architectures. This straightforward concept could establish a promising route to the design of 3D elements for future nano-electronic devices.

  14. High-purity 3D nano-objects grown by focused-electron-beam induced deposition.

    PubMed

    Córdoba, Rosa; Sharma, Nidhi; Kölling, Sebastian; Koenraad, Paul M; Koopmans, Bert

    2016-09-01

    To increase the efficiency of current electronics, a specific challenge for the next generation of memory, sensing and logic devices is to find suitable strategies to move from two- to three-dimensional (3D) architectures. However, the creation of real 3D nano-objects is not trivial. Emerging non-conventional nanofabrication tools are required for this purpose. One attractive method is focused-electron-beam induced deposition (FEBID), a direct-write process of 3D nano-objects. Here, we grow 3D iron and cobalt nanopillars by FEBID using diiron nonacarbonyl Fe2(CO)9, and dicobalt octacarbonyl Co2(CO)8, respectively, as starting materials. In addition, we systematically study the composition of these nanopillars at the sub-nanometer scale by atom probe tomography, explicitly mapping the homogeneity of the radial and longitudinal composition distributions. We show a way of fabricating high-purity 3D vertical nanostructures of ∼50 nm in diameter and a few micrometers in length. Our results suggest that the purity of such 3D nanoelements (above 90 at% Fe and above 95 at% Co) is directly linked to their growth regime, in which the selected deposition conditions are crucial for the final quality of the nanostructure. Moreover, we demonstrate that FEBID and the proposed characterization technique not only allow for growth and chemical analysis of single-element structures, but also offers a new way to directly study 3D core-shell architectures. This straightforward concept could establish a promising route to the design of 3D elements for future nano-electronic devices. PMID:27454835

  15. A neuromorphic system for video object recognition

    PubMed Central

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  16. A neuromorphic system for video object recognition.

    PubMed

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  17. Automatic 360-deg profilometry of a 3D object using a shearing interferometer and virtual grating

    NASA Astrophysics Data System (ADS)

    Zhang, Yong-Lin; Bu, Guixue

    1996-10-01

    Phase measuring technique has been widely used in optical precision inspection for its extraordinary advantage. We use the phase-measuring technique and design a practical instrument for measuring 360 degrees profile of 3D object. A novel method that can realize profile detection with higher speed and lower cost is proposed. Phase unwrapping algorithm based on the second order differentiation is developed. A complete 3D shape is reconstructed from a series of line- section profiles corresponding to discrete angular position of the object. The profile-jointing procedure is only related with two fixed parameters and coordination transformation.

  18. 3D-Web-GIS RFID Location Sensing System for Construction Objects

    PubMed Central

    2013-01-01

    Construction site managers could benefit from being able to visualize on-site construction objects. Radio frequency identification (RFID) technology has been shown to improve the efficiency of construction object management. The objective of this study is to develop a 3D-Web-GIS RFID location sensing system for construction objects. An RFID 3D location sensing algorithm combining Simulated Annealing (SA) and a gradient descent method is proposed to determine target object location. In the algorithm, SA is used to stabilize the search process and the gradient descent method is used to reduce errors. The locations of the analyzed objects are visualized using the 3D-Web-GIS system. A real construction site is used to validate the applicability of the proposed method, with results indicating that the proposed approach can provide faster, more accurate, and more stable 3D positioning results than other location sensing algorithms. The proposed system allows construction managers to better understand worksite status, thus enhancing managerial efficiency. PMID:23864821

  19. Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning

    NASA Astrophysics Data System (ADS)

    Serna, Andrés; Marcotegui, Beatriz

    2014-07-01

    We propose an automatic and robust approach to detect, segment and classify urban objects from 3D point clouds. Processing is carried out using elevation images and the result is reprojected onto the 3D point cloud. First, the ground is segmented and objects are detected as discontinuities on the ground. Then, connected objects are segmented using a watershed approach. Finally, objects are classified using SVM with geometrical and contextual features. Our methodology is evaluated on databases from Ohio (USA) and Paris (France). In the former, our method detects 98% of the objects, 78% of them are correctly segmented and 82% of the well-segmented objects are correctly classified. In the latter, our method leads to an improvement of about 15% on the classification step with respect to previous works. Quantitative results prove that our method not only provides a good performance but is also faster than other works reported in the literature.

  20. 3D shape shearography with integrated structured light projection for strain inspection of curved objects

    NASA Astrophysics Data System (ADS)

    Anisimov, Andrei G.; Groves, Roger M.

    2015-05-01

    Shearography (speckle pattern shearing interferometry) is a non-destructive testing technique that provides full-field surface strain characterization. Although real-life objects especially in aerospace, transport or cultural heritage are not flat (e.g. aircraft leading edges or sculptures), their inspection with shearography is of interest for both hidden defect detection and material characterization. Accurate strain measuring of a highly curved or free form surface needs to be performed by combining inline object shape measuring and processing of shearography data in 3D. Previous research has not provided a general solution. This research is devoted to the practical questions of 3D shape shearography system development for surface strain characterization of curved objects. The complete procedure of calibration and data processing of a 3D shape shearography system with integrated structured light projector is presented. This includes an estimation of the actual shear distance and a sensitivity matrix correction within the system field of view. For the experimental part a 3D shape shearography system prototype was developed. It employs three spatially-distributed shearing cameras, with Michelson interferometers acting as the shearing devices, one illumination laser source and a structured light projector. The developed system performance was evaluated with a previously reported cylinder specimen (length 400 mm, external diameter 190 mmm) loaded by internal pressure. Further steps for the 3D shape shearography prototype and the technique development are also proposed.

  1. Object recognition by artificial cortical maps.

    PubMed

    Plebe, Alessio; Domenella, Rosaria Grazia

    2007-09-01

    Object recognition is one of the most important functions of the human visual system, yet one of the least understood, this despite the fact that vision is certainly the most studied function of the brain. We understand relatively well how several processes in the cortical visual areas that support recognition capabilities take place, such as orientation discrimination and color constancy. This paper proposes a model of the development of object recognition capability, based on two main theoretical principles. The first is that recognition does not imply any sort of geometrical reconstruction, it is instead fully driven by the two dimensional view captured by the retina. The second assumption is that all the processing functions involved in recognition are not genetically determined or hardwired in neural circuits, but are the result of interactions between epigenetic influences and basic neural plasticity mechanisms. The model is organized in modules roughly related to the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent neural self-organizing map model that simulates the effects of intercortical lateral connections. This paper shows how recognition capabilities, similar to those found in brain ventral visual areas, can develop spontaneously by exposure to natural images in an artificial cortical model. PMID:17604954

  2. Hybrid pyramid/neural network object recognition

    NASA Astrophysics Data System (ADS)

    Anandan, P.; Burt, Peter J.; Pearson, John C.; Spence, Clay D.

    1994-02-01

    This work concerns computationally efficient computer vision methods for the search for and identification of small objects in large images. The approach combines neural network pattern recognition with pyramid-based coarse-to-fine search, in a way that eliminates the drawbacks of each method when used by itself and, in addition, improves object identification through learning and exploiting the low-resolution image context associated with the objects. The presentation will describe the system architecture and the performance on illustrative problems.

  3. Street curb recognition in 3d point cloud data using morphological operations

    NASA Astrophysics Data System (ADS)

    Rodríguez-Cuenca, Borja; Concepción Alonso-Rodríguez, María; García-Cortés, Silverio; Ordóñez, Celestino

    2015-04-01

    Accurate and automatic detection of cartographic-entities saves a great deal of time and money when creating and updating cartographic databases. The current trend in remote sensing feature extraction is to develop methods that are as automatic as possible. The aim is to develop algorithms that can obtain accurate results with the least possible human intervention in the process. Non-manual curb detection is an important issue in road maintenance, 3D urban modeling, and autonomous navigation fields. This paper is focused on the semi-automatic recognition of curbs and street boundaries using a 3D point cloud registered by a mobile laser scanner (MLS) system. This work is divided into four steps. First, a coordinate system transformation is carried out, moving from a global coordinate system to a local one. After that and in order to simplify the calculations involved in the procedure, a rasterization based on the projection of the measured point cloud on the XY plane was carried out, passing from the 3D original data to a 2D image. To determine the location of curbs in the image, different image processing techniques such as thresholding and morphological operations were applied. Finally, the upper and lower edges of curbs are detected by an unsupervised classification algorithm on the curvature and roughness of the points that represent curbs. The proposed method is valid in both straight and curved road sections and applicable both to laser scanner and stereo vision 3D data due to the independence of its scanning geometry. This method has been successfully tested with two datasets measured by different sensors. The first dataset corresponds to a point cloud measured by a TOPCON sensor in the Spanish town of Cudillero. That point cloud comprises more than 6,000,000 points and covers a 400-meter street. The second dataset corresponds to a point cloud measured by a RIEGL sensor in the Austrian town of Horn. That point cloud comprises 8,000,000 points and represents a

  4. Holographic display of real existing objects from their 3D Fourier spectrum

    NASA Astrophysics Data System (ADS)

    Yatagai, Toyohiko; Sando, Yusuke

    2005-02-01

    A method for synthesizing computer-generated holograms of real-existing objects is described. A series of projection images are recorded both vertically and horizontally with an incoherent light source and a color CCD camera. According to the principle of computer tomography(CT), the 3-D Fourier spectrum is calculated from several projection images of objects and the Fresnel computer-generated hologram(CGH) is synthesized using a part of the 3-D Fourier spectrum. This method has following advantages. At first, no-blur reconstructed images in any direction are obtained owing to two-dimensionally scanning in recording. Secondarily, since not interference fringes but simple projection images of objects are recorded, a coherent light source is not necessary for recording. The use of a color CCD in recording enables us to record and reconstruct colorful objects. Finally, we demonstrate color reconstruction of objects both numerically and optically.

  5. A Skeleton-Based 3D Shape Reconstruction of Free-Form Objects with Stereo Vision

    NASA Astrophysics Data System (ADS)

    Saini, Deepika; Kumar, Sanjeev

    2015-12-01

    In this paper, an efficient approach is proposed for recovering the 3D shape of a free-form object from its arbitrary pair of stereo images. In particular, the reconstruction problem is treated as the reconstruction of the skeleton and the external boundary of the object. The reconstructed skeleton is termed as the line-like representation or curve-skeleton of the 3D object. The proposed solution for object reconstruction is based on this evolved curve-skeleton. It is used as a seed for recovering shape of the 3D object, and the extracted boundary is used for terminating the growing process of the object. NURBS-skeleton is used to extract the skeleton of both views. Affine invariant property of the convex hulls is used to establish the correspondence between the skeletons and boundaries in the stereo images. In the growing process, a distance field is defined for each skeleton point as the smallest distance from that point to the boundary of the object. A sphere centered at a skeleton point of radius equal to the minimum distance to the boundary is tangential to the boundary. Filling in the spheres centered at each skeleton point reconstructs the object. Several results are presented in order to check the applicability and validity of the proposed algorithm.

  6. 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. PMID:25802154

  7. 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

  8. Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications

    NASA Astrophysics Data System (ADS)

    Budzan, Sebastian; Kasprzyk, Jerzy

    2016-02-01

    The problem of obstacle detection and recognition or, generally, scene mapping is one of the most investigated problems in computer vision, especially in mobile applications. In this paper a fused optical system using depth information with color images gathered from the Microsoft Kinect sensor and 3D laser range scanner data is proposed for obstacle detection and ground estimation in real-time mobile systems. The algorithm consists of feature extraction in the laser range images, processing of the depth information from the Kinect sensor, fusion of the sensor information, and classification of the data into two separate categories: road and obstacle. Exemplary results are presented and it is shown that fusion of information gathered from different sources increases the effectiveness of the obstacle detection in different scenarios, and it can be used successfully for road surface mapping.

  9. Analyzing the relevance of shape descriptors in automated recognition of facial gestures in 3D images

    NASA Astrophysics Data System (ADS)

    Rodriguez A., Julian S.; Prieto, Flavio

    2013-03-01

    The present document shows and explains the results from analyzing shape descriptors (DESIRE and Spherical Spin Image) for facial recognition of 3D images. DESIRE is a descriptor made of depth images, silhouettes and rays extended from a polygonal mesh; whereas the Spherical Spin Image (SSI) associated to a polygonal mesh point, is a 2D histogram built from neighboring points by using the position information that captures features of the local shape. The database used contains images of facial expressions which in average were recognized 88.16% using a neuronal network and 91.11% with a Bayesian classifier in the case of the first descriptor; in contrast, the second descriptor only recognizes in average 32% and 23,6% using the same mentioned classifiers respectively.

  10. Modeling and modification of medical 3D objects. The benefit of using a haptic modeling tool.

    PubMed

    Kling-Petersen, T; Rydmark, M

    2000-01-01

    any given amount of smoothing to the object. While the final objects need to be exported for further 3D graphic manipulation, FreeForm addresses one of the most time consuming problems of 3D modeling: modification and creation of non-geometric 3D objects. PMID:10977532

  11. Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

    SciTech Connect

    Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; Shochet, M.; Tang, F.; Demarteau, M.; /Argonne /INFN, Padova

    2011-04-13

    Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition

  12. 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.

  13. Fast error simulation of optical 3D measurements at translucent objects

    NASA Astrophysics Data System (ADS)

    Lutzke, P.; Kühmstedt, P.; Notni, G.

    2012-09-01

    The scan results of optical 3D measurements at translucent objects deviate from the real objects surface. This error is caused by the fact that light is scattered in the objects volume and is not exclusively reflected at its surface. A few approaches were made to separate the surface reflected light from the volume scattered. For smooth objects the surface reflected light is dominantly concentrated in specular direction and could only be observed from a point in this direction. Thus the separation either leads to measurement results only creating data for near specular directions or provides data from not well separated areas. To ensure the flexibility and precision of optical 3D measurement systems for translucent materials it is necessary to enhance the understanding of the error forming process. For this purpose a technique for simulating the 3D measurement at translucent objects is presented. A simple error model is shortly outlined and extended to an efficient simulation environment based upon ordinary raytracing methods. In comparison the results of a Monte-Carlo simulation are presented. Only a few material and object parameters are needed for the raytracing simulation approach. The attempt of in-system collection of these material and object specific parameters is illustrated. The main concept of developing an error-compensation method based on the simulation environment and the collected parameters is described. The complete procedure is using both, the surface reflected and the volume scattered light for further processing.

  14. 3D face recognition using simulated annealing and the surface interpenetration measure.

    PubMed

    Queirolo, Chauã C; Silva, Luciano; Bellon, Olga R P; Segundo, Maurício Pamplona

    2010-02-01

    This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a Simulated Annealing-based approach (SA) for range image registration with the Surface Interpenetration Measure (SIM), as similarity measure, in order to match two face images. The authentication score is obtained by combining the SIM values corresponding to the matching of four different face regions: circular and elliptical areas around the nose, forehead, and the entire face region. Then, a modified SA approach is proposed taking advantage of invariant face regions to better handle facial expressions. Comprehensive experiments were performed on the FRGC v2 database, the largest available database of 3D face images composed of 4,007 images with different facial expressions. The experiments simulated both verification and identification systems and the results compared to those reported by state-of-the-art works. By using all of the images in the database, a verification rate of 96.5 percent was achieved at a False Acceptance Rate (FAR) of 0.1 percent. In the identification scenario, a rank-one accuracy of 98.4 percent was achieved. To the best of our knowledge, this is the highest rank-one score ever achieved for the FRGC v2 database when compared to results published in the literature. PMID:20075453

  15. Printing of metallic 3D micro-objects by laser induced forward transfer.

    PubMed

    Zenou, Michael; Kotler, Zvi

    2016-01-25

    Digital printing of 3D metal micro-structures by laser induced forward transfer under ambient conditions is reviewed. Recent progress has allowed drop on demand transfer of molten, femto-liter, metal droplets with a high jetting directionality. Such small volume droplets solidify instantly, on a nanosecond time scale, as they touch the substrate. This fast solidification limits their lateral spreading and allows the fabrication of high aspect ratio and complex 3D metal structures. Several examples of micron-scale resolution metal objects printed using this method are presented and discussed. PMID:26832524

  16. Close-Range Photogrammetric Tools for Small 3d Archeological Objects

    NASA Astrophysics Data System (ADS)

    Samaan, M.; Héno, R.; Pierrot-Deseilligny, M.

    2013-07-01

    This article will focus on the first experiments carried out for our PHD thesis, which is meant to make the new image-based methods available for archeologists. As a matter of fact, efforts need to be made to find cheap, efficient and user-friendly procedures for image acquisition, data processing and quality control. Among the numerous tasks that archeologists have to face daily is the 3D recording of very small objects. The Apero/MicMac tools were used for the georeferencing and the dense correlation procedures. Relatively standard workflows lead to depth maps, which can be represented either as 3D point clouds or shaded relief images.

  17. Timecourse of neural signatures of object recognition.

    PubMed

    Johnson, Jeffrey S; Olshausen, Bruno A

    2003-01-01

    How long does it take for the human visual system to recognize objects? This issue is important for understanding visual cortical function as it places constraints on models of the information processing underlying recognition. We designed a series of event-related potential (ERP) experiments to measure the timecourse of electrophysiological correlates of object recognition. We find two distinct types of components in the ERP recorded during categorization of natural images. One is an early presentation-locked signal arising around 135 ms that is present when there are low-level feature differences between images. The other is a later, recognition-related component arising between 150-300 ms. Unlike the early component, the latency of the later component covaries with the subsequent reaction time. In contrast to previous studies suggesting that the early, presentation-locked component of neural activity is correlated to recognition, these results imply that the neural signatures of recognition have a substantially later and variable time of onset. PMID:14507255

  18. Robust Detection of Round Shaped Pits Lying on 3D Meshes: Application to Impact Crater Recognition

    NASA Astrophysics Data System (ADS)

    Schmidt, Martin-Pierre; Muscato, Jennifer; Viseur, Sophie; Jorda, Laurent; Bouley, Sylvain; Mari, Jean-Luc

    2015-04-01

    Most celestial bodies display impacts of collisions with asteroids and meteoroids. These traces are called craters. The possibility of observing and identifying these craters and their characteristics (radius, depth and morphology) is the only method available to measure the age of different units at the surface of the body, which in turn allows to constrain its conditions of formation. Interplanetary space probes always carry at least one imaging instrument on board. The visible images of the target are used to reconstruct high-resolution 3D models of its surface as a cloud of points in the case of multi-image dense stereo, or as a triangular mesh in the case of stereo and shape-from-shading. The goal of this work is to develop a methodology to automatically detect the craters lying on these 3D models. The robust extraction of feature areas on surface objects embedded in 3D, like circular pits, is a challenging problem. Classical approaches generally rely on image processing and template matching on a 2D flat projection of the 3D object (i.e.: a high-resolution photograph). In this work, we propose a full-3D method that mainly relies on curvature analysis. Mean and Gaussian curvatures are estimated on the surface. They are used to label vertices that belong to concave parts corresponding to specific pits on the surface. The surface is thus transformed into binary map distinguishing potential crater features to other types of features. Centers are located in the targeted surface regions, corresponding to potential crater features. Concentric rings are then built around the found centers. They consist in circular closed lines exclusively composed of edges of the initial mesh. The first built ring represents the nearest vertex neighborhood of the found center. The ring is then optimally expanded using a circularity constrain and the curvature values of the ring vertices. This method has been tested on a 3D model of the asteroid Lutetia observed by the ROSETTA (ESA

  19. The Visual Representation of 3D Object Orientation in Parietal Cortex

    PubMed Central

    Cowan, Noah J.; Angelaki, Dora E.

    2013-01-01

    An accurate representation of three-dimensional (3D) object orientation is essential for interacting with the environment. Where and how the brain visually encodes 3D object orientation remains unknown, but prior studies suggest the caudal intraparietal area (CIP) may be involved. Here, we develop rigorous analytical methods for quantifying 3D orientation tuning curves, and use these tools to the study the neural coding of surface orientation. Specifically, we show that single neurons in area CIP of the rhesus macaque jointly encode the slant and tilt of a planar surface, and that across the population, the distribution of preferred slant-tilts is not statistically different from uniform. This suggests that all slant-tilt combinations are equally represented in area CIP. Furthermore, some CIP neurons are found to also represent the third rotational degree of freedom that determines the orientation of the image pattern on the planar surface. Together, the present results suggest that CIP is a critical neural locus for the encoding of all three rotational degrees of freedom specifying an object's 3D spatial orientation. PMID:24305830

  20. Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

    NASA Astrophysics Data System (ADS)

    Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

    2010-07-01

    The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

  1. Systems in Development: Motor Skill Acquisition Facilitates 3D Object Completion

    PubMed Central

    Soska, Kasey C.; Adolph, Karen E.; Johnson, Scott P.

    2009-01-01

    How do infants learn to perceive the backs of objects that they see only from a limited viewpoint? Infants’ 3D object completion abilities emerge in conjunction with developing motor skills—independent sitting and visual-manual exploration. Twenty-eight 4.5- to 7.5-month-old infants were habituated to a limited-view object and tested with volumetrically complete and incomplete (hollow) versions of the same object. Parents reported infants’ sitting experience, and infants’ visual-manual exploration of objects was observed in a structured play session. Infants’ self-sitting experience and visual-manual exploratory skills predicted looking to the novel, incomplete object on the habituation task. Further analyses revealed that self-sitting facilitated infants’ visual inspection of objects while they manipulated them. The results are framed within a developmental systems approach, wherein infants’ sitting skill, multimodal object exploration, and object knowledge are linked in developmental time. PMID:20053012

  2. CAD/CAM/CAE representation of 3D objects measured by fringe projection

    NASA Astrophysics Data System (ADS)

    Pancewicz, Tomasz; Kujawinska, Malgorzata

    1998-07-01

    In the paper the creation of a virtual object on the base of optical measurement of 3D object by fringe projection technique coupled with the capabilities of CAD systems is presented. Basic stages of that task, being the most important part of the reverse engineering process, are discussed and the procedure is formulated by terms and definitions of theory of optimal algorithms. The quality criteria of a virtual object are defined and the influence of consecutive stages of the task on the quality of the virtual object is discussed.

  3. The effect of background and illumination on color identification of real, 3D objects

    PubMed Central

    Allred, Sarah R.; Olkkonen, Maria

    2013-01-01

    For the surface reflectance of an object to be a useful cue to object identity, judgments of its color should remain stable across changes in the object's environment. In 2D scenes, there is general consensus that color judgments are much more stable across illumination changes than background changes. Here we investigate whether these findings generalize to real 3D objects. Observers made color matches to cubes as we independently varied both the illumination impinging on the cube and the 3D background of the cube. As in 2D scenes, we found relatively high but imperfect stability of color judgments under an illuminant shift. In contrast to 2D scenes, we found that background had little effect on average color judgments. In addition, variability of color judgments was increased by an illuminant shift and decreased by embedding the cube within a background. Taken together, these results suggest that in real 3D scenes with ample cues to object segregation, the addition of a background may improve stability of color identification. PMID:24273521

  4. a Low-Cost and Portable System for 3d Reconstruction of Texture-Less Objects

    NASA Astrophysics Data System (ADS)

    Hosseininaveh, A.; Yazdan, R.; Karami, A.; Moradi, M.; Ghorbani, F.

    2015-12-01

    The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.

  5. Approximation of a foreign object using x-rays, reference photographs and 3D reconstruction techniques.

    PubMed

    Briggs, Matt; Shanmugam, Mohan

    2013-12-01

    This case study describes how a 3D animation was created to approximate the depth and angle of a foreign object (metal bar) that had become embedded into a patient's head. A pre-operative CT scan was not available as the patient could not fit though the CT scanner, therefore a post surgical CT scan, x-ray and photographic images were used. A surface render was made of the skull and imported into Blender (a 3D animation application). The metal bar was not available, however images of a similar object that was retrieved from the scene by the ambulance crew were used to recreate a 3D model. The x-ray images were then imported into Blender and used as background images in order to align the skull reconstruction and metal bar at the correct depth/angle. A 3D animation was then created to fully illustrate the angle and depth of the iron bar in the skull. PMID:24206011

  6. Event-related potential (ERP) indices of infants’ recognition of familiar and unfamiliar objects in two and three dimensions

    PubMed Central

    Carver, Leslie J.; Meltzoff, Andrew N.; Dawson, Geraldine

    2006-01-01

    We measured infants’ recognition of familiar and unfamiliar 3-D objects and their 2-D representations using event-related potentials (ERPs). Infants differentiated familiar from unfamiliar objects when viewing them in both two and three dimensions. However, differentiation between the familiar and novel objects occurred more quickly when infants viewed the object in 3-D than when they viewed 2-D representations. The results are discussed with respect to infants’ recognition abilities and their understanding of real objects and representations. This is the first study using 3-D objects in conjunction with ERPs in infants, and it introduces an interesting new methodology for assessing infants’ electrophysiological responses to real objects. PMID:16445396

  7. A novel method of target recognition based on 3D-color-space locally adaptive regression kernels model

    NASA Astrophysics Data System (ADS)

    Liu, Jiaqi; Han, Jing; Zhang, Yi; Bai, Lianfa

    2015-10-01

    Locally adaptive regression kernels model can describe the edge shape of images accurately and graphic trend of images integrally, but it did not consider images' color information while the color is an important element of an image. Therefore, we present a novel method of target recognition based on 3-D-color-space locally adaptive regression kernels model. Different from the general additional color information, this method directly calculate the local similarity features of 3-D data from the color image. The proposed method uses a few examples of an object as a query to detect generic objects with incompact, complex and changeable shapes. Our method involves three phases: First, calculating the novel color-space descriptors from the RGB color space of query image which measure the likeness of a voxel to its surroundings. Salient features which include spatial- dimensional and color -dimensional information are extracted from said descriptors, and simplifying them to construct a non-similar local structure feature set of the object class by principal components analysis (PCA). Second, we compare the salient features with analogous features from the target image. This comparison is done using a matrix generalization of the cosine similarity measure. Then the similar structures in the target image are obtained using local similarity structure statistical matching. Finally, we use the method of non-maxima suppression in the similarity image to extract the object position and mark the object in the test image. Experimental results demonstrate that our approach is effective and accurate in improving the ability to identify targets.

  8. 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

  9. Object recognition with hierarchical discriminant saliency networks

    PubMed Central

    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

  10. Explanation mode for Bayesian automatic object recognition

    NASA Astrophysics Data System (ADS)

    Hazlett, Thomas L.; Cofer, Rufus H.; Brown, Harold K.

    1992-09-01

    One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision--a very 'expert system' like capability. When various sources of incoming data are represented by C++ classes, it becomes possible to automatically backtrack the Bayesian data fusion process, assigning relative weights to the more significant datums and their combinations. A C++ object oriented engine is then able to synthesize 'English' like textural description of the Bayesian reasoning suitable for generalized presentation. Key concepts and examples are provided based on an actual object recognition problem.

  11. Registration of untypical 3D objects in Polish cadastre - do we need 3D cadastre? / Rejestracja nietypowych obiektów 3D w polskim katastrze - czy istnieje potrzeba wdrożenia katastru 3D?

    NASA Astrophysics Data System (ADS)

    Marcin, Karabin

    2012-11-01

    Polish cadastral system consists of two registers: cadastre and land register. The cadastre register data on cadastral objects (land, buildings and premises) in particular location (in a two-dimensional coordinate system) and their attributes as well as data about the owners. The land register contains data concerned ownerships and other rights to the property. Registration of a land parcel without spatial objects located on the surface is not problematic. Registration of buildings and premises in typical cases is not a problem either. The situation becomes more complicated in cases of multiple use of space above the parcel and with more complex construction of the buildings. The paper presents rules concerning the registration of various untypical 3D objects located within the city of Warsaw. The analysis of the data concerning those objects registered in the cadastre and land register is presented in the paper. And this is the next part of the author's detailed research. The aim of this paper is to answer the question if we really need 3D cadastre in Poland. Polski system katastralny składa się z dwóch rejestrów: ewidencji gruntów i budynków (katastru nieruchomosci) oraz ksiąg wieczystych. W ewidencji gruntów i budynków (katastrze nieruchomości) rejestrowane są dane o położeniu (w dwuwymiarowym układzie współrzędnych), atrybuty oraz dane o właścicielach obiektów katastralnych (działek, budynków i lokali), w księgach wieczystych oprócz danych właścicielskich, inne prawa do nieruchomości. Rejestracja działki bez obiektów przestrzennych położonych na jej powierzchni nie stanowi problemu. Także rejestracja budynków i lokali w typowych przypadkach nie stanowi trudności. Sytuacja staje się bardziej skomplikowana w przypadku wielokrotnego użytkowania przestrzeni powyzej lub poniżej powierzchni działki oraz w przypadku budynków o złożonej konstrukcji. W artykule przedstawiono zasady związane z rejestracją nietypowych obiektów 3

  12. 220GHz wideband 3D imaging radar for concealed object detection technology development and phenomenology studies

    NASA Astrophysics Data System (ADS)

    Robertson, Duncan A.; Macfarlane, David G.; Bryllert, Tomas

    2016-05-01

    We present a 220 GHz 3D imaging `Pathfinder' radar developed within the EU FP7 project CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) which has been built to address two objectives: (i) to de-risk the radar hardware development and (ii) to enable the collection of phenomenology data with ~1 cm3 volumetric resolution. The radar combines a DDS-based chirp generator and self-mixing multiplier technology to achieve a 30 GHz bandwidth chirp with such high linearity that the raw point response is close to ideal and only requires minor nonlinearity compensation. The single transceiver is focused with a 30 cm lens mounted on a gimbal to acquire 3D volumetric images of static test targets and materials.

  13. 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.

  14. Minimal camera networks for 3D image based modeling of cultural heritage objects.

    PubMed

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

  15. Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

    PubMed Central

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

  16. The representation of moving 3-D objects in apparent motion perception.

    PubMed

    Hidaka, Souta; Kawachi, Yousuke; Gyoba, Jiro

    2009-08-01

    In the present research, we investigated the depth information contained in the representations of apparently moving 3-D objects. By conducting three experiments, we measured the magnitude of representational momentum (RM) as an index of the consistency of an object's representation. Experiment 1A revealed that RM magnitude was greater when shaded, convex, apparently moving objects shifted to a flat circle than when they shifted to a shaded, concave, hemisphere. The difference diminished when the apparently moving objects were concave hemispheres (Experiment 1B). Using luminance-polarized circles, Experiment 2 confirmed that these results were not due to the luminance information of shading. Experiment 3 demonstrated that RM magnitude was greater when convex apparently moving objects shifted to particular blurred convex hemispheres with low-pass filtering than when they shifted to concave hemispheres. These results suggest that the internal object's representation in apparent motion contains incomplete depth information intermediate between that of 2-D and 3-D objects, particularly with regard to convexity information with low-spatial-frequency components. PMID:19633345

  17. An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

    PubMed

    Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

    2013-01-01

    Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

  18. Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

    PubMed Central

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

  19. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    PubMed

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

  20. Applying Mean-Shift - Clustering for 3D object detection in remote sensing data

    NASA Astrophysics Data System (ADS)

    Simon, Jürgen-Lorenz; Diederich, Malte; Troemel, Silke

    2013-04-01

    The timely warning and forecasting of high-impact weather events is crucial for life, safety and economy. Therefore, the development and improvement of methods for detection and nowcasting / short-term forecasting of these events is an ongoing research question. A new 3D object detection and tracking algorithm is presented. Within the project "object-based analysis and seamless predictin (OASE)" we address a better understanding and forecasting of convective events based on the synergetic use of remotely sensed data and new methods for detection, nowcasting, validation and assimilation. In order to gain advanced insight into the lifecycle of convective cells, we perform an object-detection on a new high-resolution 3D radar- and satellite based composite and plan to track the detected objects over time, providing us with a model of the lifecycle. The insights in the lifecycle will be used in order to improve prediction of convective events in the nowcasting time scale, as well as a new type of data to be assimilated into numerical weather models, thus seamlessly bridging the gap between nowcasting and NWP.. The object identification (or clustering) is performed using a technique borrowed from computer vision, called mean-shift clustering. Mean-Shift clustering works without many of the parameterizations or rigid threshold schemes employed by many existing schemes (e. g. KONRAD, TITAN, Trace-3D), which limit the tracking to fully matured, convective cells of significant size and/or strength. Mean-Shift performs without such limiting definitions, providing a wider scope for studying larger classes of phenomena and providing a vehicle for research into the object definition itself. Since the mean-shift clustering technique could be applied on many types of remote-sensing and model data for object detection, it is of general interest to the remote sensing and modeling community. The focus of the presentation is the introduction of this technique and the results of its

  1. Determining the 3-D structure and motion of objects using a scanning laser range sensor

    NASA Technical Reports Server (NTRS)

    Nandhakumar, N.; Smith, Philip W.

    1993-01-01

    In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

  2. Determining canonical views of 3D object using minimum description length criterion and compressive sensing method

    NASA Astrophysics Data System (ADS)

    Chen, Ping-Feng; Krim, Hamid

    2008-02-01

    In this paper, we propose using two methods to determine the canonical views of 3D objects: minimum description length (MDL) criterion and compressive sensing method. MDL criterion searches for the description length that achieves the balance between model accuracy and parsimony. It takes the form of the sum of a likelihood and a penalizing term, where the likelihood is in favor of model accuracy such that more views assists the description of an object, while the second term penalizes lengthy description to prevent overfitting of the model. In order to devise the likelihood term, we propose a model to represent a 3D object as the weighted sum of multiple range images, which is used in the second method to determine the canonical views as well. In compressive sensing method, an intelligent way of parsimoniously sampling an object is presented. We make direct inference from Donoho1 and Candes'2 work, and adapt it to our model. Each range image is viewed as a projection, or a sample, of a 3D model, and by using compressive sensing theory, we are able to reconstruct the object with an overwhelming probability by scarcely sensing the object in a random manner. Compressive sensing is different from traditional compressing method in the sense that the former compress things in the sampling stage while the later collects a large number of samples and then compressing mechanism is carried out thereafter. Compressive sensing scheme is particularly useful when the number of sensors are limited or the sampling machinery cost much resource or time.

  3. 3D object optonumerical acquisition methods for CAD/CAM and computer graphics systems

    NASA Astrophysics Data System (ADS)

    Sitnik, Robert; Kujawinska, Malgorzata; Pawlowski, Michal E.; Woznicki, Jerzy M.

    1999-08-01

    The creation of a virtual object for CAD/CAM and computer graphics on the base of data gathered by full-field optical measurement of 3D object is presented. The experimental co- ordinates are alternatively obtained by combined fringe projection/photogrammetry based system or fringe projection/virtual markers setup. The new and fully automatic procedure which process the cloud of measured points into triangular mesh accepted by CAD/CAM and computer graphics systems is presented. Its applicability for various classes of objects is tested including the error analysis of virtual objects generated. The usefulness of the method is proved by applying the virtual object in rapid prototyping system and in computer graphics environment.

  4. Object Recognition by a Hopfield Neural Network

    NASA Astrophysics Data System (ADS)

    Li, Wei; Nasrabadi, Nasser M.

    1990-03-01

    A model-based object recognition technique is introduced in this paper to identify and locate an object in any position and orientation. The test scenes could consist of an isolated object or several partially overlapping objects. A cooperative feature matching technique is proposed which is implemented by a Hopfield neural network. The proposed matching technique uses the parallelism of the neural network to globally match all the objects (they may be overlapping or touching) in the input scene against all the object models in the model-database at the same time. For each model, distinct features such as curvature points (corners) are extracted and a graph consisting of a number of nodes connected by arcs is constructed. Each node in the graph represents a feature which has a numerical feature value and is connected to other nodes by an arc representing the relationship or compatibility between them. Object recognition is formulated as matching a global model graph, representing all the object models, with an input scene graph representing a single object or several overlapping objects. A 2-dimensional Hopfield binary neural network is implemented to perform a subgraph isomorphism to obtain the optimal compatible matching features between the two graphs. The synaptic interconnection weights between neurons are designed such that matched features belonging to the same model receive excitatory supports, and matched features belonging to different models receive an inhibitory support or a mutual support depending on whether the input scene is an isolated object or several overlapping objects. The coordinate transformation for mapping each pair of matched nodes from the model onto the input scene is calculated, followed by a simple clustering technique to eliminate any false matches. The orientation and the position of objects in the scene are then calculated by averaging the transformation of correct matched nodes. Some simulation results are shown to illustrate the

  5. Differential and relaxed image foresting transform for graph-cut segmentation of multiple 3D objects.

    PubMed

    Moya, Nikolas; Falcão, Alexandre X; Ciesielski, Krzysztof C; Udupa, Jayaram K

    2014-01-01

    Graph-cut algorithms have been extensively investigated for interactive binary segmentation, when the simultaneous delineation of multiple objects can save considerable user's time. We present an algorithm (named DRIFT) for 3D multiple object segmentation based on seed voxels and Differential Image Foresting Transforms (DIFTs) with relaxation. DRIFT stands behind efficient implementations of some state-of-the-art methods. The user can add/remove markers (seed voxels) along a sequence of executions of the DRIFT algorithm to improve segmentation. Its first execution takes linear time with the image's size, while the subsequent executions for corrections take sublinear time in practice. At each execution, DRIFT first runs the DIFT algorithm, then it applies diffusion filtering to smooth boundaries between objects (and background) and, finally, it corrects possible objects' disconnection occurrences with respect to their seeds. We evaluate DRIFT in 3D CT-images of the thorax for segmenting the arterial system, esophagus, left pleural cavity, right pleural cavity, trachea and bronchi, and the venous system. PMID:25333179

  6. Invariant visual object recognition: biologically plausible approaches.

    PubMed

    Robinson, Leigh; Rolls, Edmund T

    2015-10-01

    Key properties of inferior temporal cortex neurons are described, and then, the biological plausibility of two leading approaches to invariant visual object recognition in the ventral visual system is assessed to investigate whether they account for these properties. Experiment 1 shows that VisNet performs object classification with random exemplars comparably to HMAX, except that the final layer C neurons of HMAX have a very non-sparse representation (unlike that in the brain) that provides little information in the single-neuron responses about the object class. Experiment 2 shows that VisNet forms invariant representations when trained with different views of each object, whereas HMAX performs poorly when assessed with a biologically plausible pattern association network, as HMAX has no mechanism to learn view invariance. Experiment 3 shows that VisNet neurons do not respond to scrambled images of faces, and thus encode shape information. HMAX neurons responded with similarly high rates to the unscrambled and scrambled faces, indicating that low-level features including texture may be relevant to HMAX performance. Experiment 4 shows that VisNet can learn to recognize objects even when the view provided by the object changes catastrophically as it transforms, whereas HMAX has no learning mechanism in its S-C hierarchy that provides for view-invariant learning. This highlights some requirements for the neurobiological mechanisms of high-level vision, and how some different approaches perform, in order to help understand the fundamental underlying principles of invariant visual object recognition in the ventral visual stream. PMID:26335743

  7. 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. PMID:26766698

  8. X-ray stereo imaging for micro 3D motions within non-transparent objects

    NASA Astrophysics Data System (ADS)

    Salih, Wasil H. M.; Buytaert, Jan A. N.; Dirckx, Joris J. J.

    2012-03-01

    We propose a new technique to measure the 3D motion of marker points along a straight path within an object using x-ray stereo projections. From recordings of two x-ray projections with 90° separation angle, the 3D coordinates of marker points can be determined. By synchronizing the x-ray exposure time to the motion event, a moving marker leaves a trace in the image of which the gray scale is linearly proportional to the marker velocity. From the gray scale along the motion path, the 3D motion (velocity) is obtained. The path of motion was reconstructed and compared with the applied waveform. The results showed that the accuracy is in order of 5%. The difference of displacement amplitude between the new method and laser vibrometry was less than 5μm. We demonstrated the method on the malleus ossicle motion in the gerbil middle ear as a function of pressure applied on the eardrum. The new method has the advantage over existing methods such as laser vibrometry that the structures under study do not need to be visually exposed. Due to the short measurement time and the high resolution, the method can be useful in the field of biomechanics for a variety of applications.

  9. Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

    NASA Astrophysics Data System (ADS)

    Alsadik, B.; Gerke, M.; Vosselman, G.

    2015-03-01

    Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

  10. Prototyping a Sensor Enabled 3d Citymodel on Geospatial Managed Objects

    NASA Astrophysics Data System (ADS)

    Kjems, E.; Kolář, J.

    2013-09-01

    One of the major development efforts within the GI Science domain are pointing at sensor based information and the usage of real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment and provide time critical information preserving our limited resources in the most sustainable way. Using 3D models with consistent object definitions give us the possibility to avoid troublesome abstractions of reality, and design even complex urban systems fusing information from various sources of data. These systems are difficult to design with the traditional software development approach based on major software packages and traditional data exchange. The data stream is varying from urban domain to urban domain and from system to system why it is almost impossible to design a complete system taking care of all thinkable instances now and in the future within one constraint software design complex. On several occasions we have been advocating for a new end advanced formulation of real world features using the concept of Geospatial Managed Objects (GMO). This paper presents the outcome of the InfraWorld project, a 4 million Euro project financed primarily by the Norwegian Research Council where the concept of GMO's have been applied in various situations on various running platforms of an urban system. The paper will be focusing on user experiences and interfaces rather then core technical and developmental issues. The project was primarily focusing on prototyping rather than realistic implementations although the results concerning applicability are quite clear.

  11. Combining laser scan and photogrammetry for 3D object modeling using a single digital camera

    NASA Astrophysics Data System (ADS)

    Xiong, Hanwei; Zhang, Hong; Zhang, Xiangwei

    2009-07-01

    In the fields of industrial design, artistic design and heritage conservation, physical objects are usually digitalized by reverse engineering through some 3D scanning methods. Laser scan and photogrammetry are two main methods to be used. For laser scan, a video camera and a laser source are necessary, and for photogrammetry, a digital still camera with high resolution pixels is indispensable. In some 3D modeling tasks, two methods are often integrated to get satisfactory results. Although many research works have been done on how to combine the results of the two methods, no work has been reported to design an integrated device at low cost. In this paper, a new 3D scan system combining laser scan and photogrammetry using a single consumer digital camera is proposed. Nowadays there are many consumer digital cameras, such as Canon EOS 5D Mark II, they usually have features of more than 10M pixels still photo recording and full 1080p HD movie recording, so a integrated scan system can be designed using such a camera. A square plate glued with coded marks is used to place the 3d objects, and two straight wood rulers also glued with coded marks can be laid on the plate freely. In the photogrammetry module, the coded marks on the plate make up a world coordinate and can be used as control network to calibrate the camera, and the planes of two rulers can also be determined. The feature points of the object and the rough volume representation from the silhouettes can be obtained in this module. In the laser scan module, a hand-held line laser is used to scan the object, and the two straight rulers are used as reference planes to determine the position of the laser. The laser scan results in dense points cloud which can be aligned together automatically through calibrated camera parameters. The final complete digital model is obtained through a new a patchwise energy functional method by fusion of the feature points, rough volume and the dense points cloud. The design

  12. Measuring the 3D shape of high temperature objects using blue sinusoidal structured light

    NASA Astrophysics Data System (ADS)

    Zhao, Xianling; Liu, Jiansheng; Zhang, Huayu; Wu, Yingchun

    2015-12-01

    The visible light radiated by some high temperature objects (less than 1200 °C) almost lies in the red and infrared waves. It will interfere with structured light projected on a forging surface if phase measurement profilometry (PMP) is used to measure the shapes of objects. In order to obtain a clear deformed pattern image, a 3D measurement method based on blue sinusoidal structured light is proposed in this present work. Moreover, a method for filtering deformed pattern images is presented for correction of the unwrapping phase. Blue sinusoidal phase-shifting fringe pattern images are projected on the surface by a digital light processing (DLP) projector, and then the deformed patterns are captured by a 3-CCD camera. The deformed pattern images are separated into R, G and B color components by the software. The B color images filtered by a low-pass filter are used to calculate the fringe order. Consequently, the 3D shape of a high temperature object is obtained by the unwrapping phase and the calibration parameter matrixes of the DLP projector and 3-CCD camera. The experimental results show that the unwrapping phase is completely corrected with the filtering method by removing the high frequency noise from the first harmonic of the B color images. The measurement system can complete the measurement in a few seconds with a relative error of less than 1 : 1000.

  13. Calibration target reconstruction for 3-D vision inspection system of large-scale engineering objects

    NASA Astrophysics Data System (ADS)

    Yin, Yongkai; Peng, Xiang; Guan, Yingjian; Liu, Xiaoli; Li, Ameng

    2010-11-01

    It is usually difficult to calibrate the 3-D vision inspection system that may be employed to measure the large-scale engineering objects. One of the challenges is how to in-situ build-up a large and precise calibration target. In this paper, we present a calibration target reconstruction strategy to solve such a problem. First, we choose one of the engineering objects to be inspected as a calibration target, on which we paste coded marks on the object surface. Next, we locate and decode marks to get homologous points. From multiple camera images, the fundamental matrix between adjacent images can be estimated, and then the essential matrix can be derived with priori known camera intrinsic parameters and decomposed to obtain camera extrinsic parameters. Finally, we are able to obtain the initial 3D coordinates with binocular stereo vision reconstruction, and then optimize them with the bundle adjustment by considering the lens distortions, leading to a high-precision calibration target. This reconstruction strategy has been applied to the inspection of an industrial project, from which the proposed method is successfully validated.

  14. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets. PMID:17671862

  15. Support plane method applied to ground objects recognition using modelled SAR images

    NASA Astrophysics Data System (ADS)

    Zherdev, Denis A.; Fursov, Vladimir A.

    2015-09-01

    In this study, the object recognition problem was solved using support plane method. The modelled SAR images were used as features vectors in the recognition algorithm. Radar signal backscattering of objects in different observing poses is presented in SAR images. For real time simulation, we used simple mixture model of Lambertian-specular reflectivity. To this end, an algorithm of ray tracing is extended for simulating SAR images of 3D man-made models. The suggested algorithm of support plane is very effective in objects recognition using SAR images and RCS diagrams.

  16. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

    PubMed

    Mateo, Carlos M; Gil, Pablo; Torres, Fernando

    2016-01-01

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID:27164102

  17. 3D Imaging with a Single-Aperture 3-mm Objective Lens: Concept, Fabrication and Test

    NASA Technical Reports Server (NTRS)

    Korniski, Ron; Bae, Sam Y.; Shearn, Mike; Manohara, Harish; Shahinian, Hrayr

    2011-01-01

    There are many advantages to minimally invasive surgery (MIS). An endoscope is the optical system of choice by the surgeon for MIS. The smaller the incision or opening made to perform the surgery, the smaller the optical system needed. For minimally invasive neurological and skull base surgeries the openings are typically 10-mm in diameter (dime sized) or less. The largest outside diameter (OD) endoscope used is 4mm. A significant drawback to endoscopic MIS is that it only provides a monocular view of the surgical site thereby lacking depth information for the surgeon. A stereo view would provide the surgeon instantaneous depth information of the surroundings within the field of view, a significant advantage especially during brain surgery. Providing 3D imaging in an endoscopic objective lens system presents significant challenges because of the tight packaging constraints. This paper presents a promising new technique for endoscopic 3D imaging that uses a single lens system with complementary multi-bandpass filters (CMBFs), and describes the proof-of-concept demonstrations performed to date validating the technique. These demonstrations of the technique have utilized many commercial off-the-shelf (COTS) components including the ones used in the endoscope objective.

  18. Object-adaptive depth compensated inter prediction for depth video coding in 3D video system

    NASA Astrophysics Data System (ADS)

    Kang, Min-Koo; Lee, Jaejoon; Lim, Ilsoon; Ho, Yo-Sung

    2011-01-01

    Nowadays, the 3D video system using the MVD (multi-view video plus depth) data format is being actively studied. The system has many advantages with respect to virtual view synthesis such as an auto-stereoscopic functionality, but compression of huge input data remains a problem. Therefore, efficient 3D data compression is extremely important in the system, and problems of low temporal consistency and viewpoint correlation should be resolved for efficient depth video coding. In this paper, we propose an object-adaptive depth compensated inter prediction method to resolve the problems where object-adaptive mean-depth difference between a current block, to be coded, and a reference block are compensated during inter prediction. In addition, unique properties of depth video are exploited to reduce side information required for signaling decoder to conduct the same process. To evaluate the coding performance, we have implemented the proposed method into MVC (multiview video coding) reference software, JMVC 8.2. Experimental results have demonstrated that our proposed method is especially efficient for depth videos estimated by DERS (depth estimation reference software) discussed in the MPEG 3DV coding group. The coding gain was up to 11.69% bit-saving, and it was even increased when we evaluated it on synthesized views of virtual viewpoints.

  19. A smoothness constraint on the development of object recognition.

    PubMed

    Wood, Justin N

    2016-08-01

    Understanding how the brain learns to recognize objects is one of the ultimate goals in the cognitive sciences. To date, however, we have not yet characterized the environmental factors that cause object recognition to emerge in the newborn brain. Here, I present the results of a high-throughput controlled-rearing experiment that examined whether the development of object recognition requires experience with temporally smooth visual objects. When newborn chicks (Gallus gallus) were raised with virtual objects that moved smoothly over time, the chicks developed accurate color recognition, shape recognition, and color-shape binding abilities. In contrast, when newborn chicks were raised with virtual objects that moved non-smoothly over time, the chicks' object recognition abilities were severely impaired. These results provide evidence for a "smoothness constraint" on newborn object recognition. Experience with temporally smooth objects facilitates the development of object recognition. PMID:27208825

  20. Active learning in the lecture theatre using 3D printed objects.

    PubMed

    Smith, David P

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

  1. Knowledge guided object detection and identification in 3D point clouds

    NASA Astrophysics Data System (ADS)

    Karmacharya, A.; Boochs, F.; Tietz, B.

    2015-05-01

    Modern instruments like laser scanner and 3D cameras or image based techniques like structure from motion produce huge point clouds as base for further object analysis. This has considerably changed the way of data compilation away from selective manually guided processes towards automatic and computer supported strategies. However it's still a long way to achieve the quality and robustness of manual processes as data sets are mostly very complex. Looking at existing strategies 3D data processing for object detections and reconstruction rely heavily on either data driven or model driven approaches. These approaches come with their limitation on depending highly on the nature of data and inability to handle any deviation. Furthermore, the lack of capabilities to integrate other data or information in between the processing steps further exposes their limitations. This restricts the approaches to be executed with strict predefined strategy and does not allow deviations when and if new unexpected situations arise. We propose a solution that induces intelligence in the processing activities through the usage of semantics. The solution binds the objects along with other related knowledge domains to the numerical processing to facilitate the detection of geometries and then uses experts' inference rules to annotate them. The solution was tested within the prototypical application of the research project "Wissensbasierte Detektion von Objekten in Punktwolken für Anwendungen im Ingenieurbereich (WiDOP)". The flexibility of the solution is demonstrated through two entirely different USE Case scenarios: Deutsche Bahn (German Railway System) for the outdoor scenarios and Fraport (Frankfort Airport) for the indoor scenarios. Apart from the difference in their environments, they provide different conditions, which the solution needs to consider. While locations of the objects in Fraport were previously known, that of DB were not known at the beginning.

  2. Active learning in the lecture theatre using 3D printed objects

    PubMed Central

    Smith, David P.

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

  3. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

    PubMed Central

    Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

    2016-01-01

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID

  4. Laser Scanning for 3D Object Characterization: Infrastructure for Exploration and Analysis of Vegetation Signatures

    NASA Astrophysics Data System (ADS)

    Koenig, K.; Höfle, B.

    2012-04-01

    Mapping and characterization of the three-dimensional nature of vegetation is increasingly gaining in importance. Deeper insight is required for e.g. forest management, biodiversity assessment, habitat analysis, precision agriculture, renewable energy production or the analysis of interaction between biosphere and atmosphere. However the potential of 3D vegetation characterization has not been exploited so far and new technologies are needed. Laser scanning has evolved into the state-of-the-art technology for highly accurate 3D data acquisition. By now several studies indicated a high value of 3D vegetation description by using laser data. The laser sensors provide a detailed geometric presentation (geometric information) of scanned objects as well as a full profile of laser energy that was scattered back to the sensor (radiometric information). In order to exploit the full potential of these datasets, profound knowledge on laser scanning technology for data acquisition, geoinformation technology for data analysis and object of interest (e.g. vegetation) for data interpretation have to be joined. A signature database is a collection of signatures of reference vegetation objects acquired under known conditions and sensor parameters and can be used to improve information extraction from unclassified vegetation datasets. Different vegetation elements (leaves, branches, etc.) at different heights above ground with different geometric composition contribute to the overall description (i.e. signature) of the scanned object. The developed tools allow analyzing tree objects according to single features (e.g. echo width and signal amplitude) and to any relation of features and derived statistical values (e.g. ratio of laser point attributes). For example, a single backscatter cross section value does not allow for tree species determination, whereas the average echo width per tree segment can give good estimates. Statistical values and/or distributions (e.g. Gaussian

  5. Correlative nanoscale 3D imaging of structure and composition in extended objects.

    PubMed

    Xu, Feng; Helfen, Lukas; Suhonen, Heikki; Elgrabli, Dan; Bayat, Sam; Reischig, Péter; Baumbach, Tilo; Cloetens, Peter

    2012-01-01

    Structure and composition at the nanoscale determine the behavior of biological systems and engineered materials. The drive to understand and control this behavior has placed strong demands on developing methods for high resolution imaging. In general, the improvement of three-dimensional (3D) resolution is accomplished by tightening constraints: reduced manageable specimen sizes, decreasing analyzable volumes, degrading contrasts, and increasing sample preparation efforts. Aiming to overcome these limitations, we present a non-destructive and multiple-contrast imaging technique, using principles of X-ray laminography, thus generalizing tomography towards laterally extended objects. We retain advantages that are usually restricted to 2D microscopic imaging, such as scanning of large areas and subsequent zooming-in towards a region of interest at the highest possible resolution. Our technique permits correlating the 3D structure and the elemental distribution yielding a high sensitivity to variations of the electron density via coherent imaging and to local trace element quantification through X-ray fluorescence. We demonstrate the method by imaging a lithographic nanostructure and an aluminum alloy. Analyzing a biological system, we visualize in lung tissue the subcellular response to toxic stress after exposure to nanotubes. We show that most of the nanotubes are trapped inside alveolar macrophages, while a small portion of the nanotubes has crossed the barrier to the cellular space of the alveolar wall. In general, our method is non-destructive and can be combined with different sample environmental or loading conditions. We therefore anticipate that correlative X-ray nano-laminography will enable a variety of in situ and in operando 3D studies. PMID:23185554

  6. Correlative Nanoscale 3D Imaging of Structure and Composition in Extended Objects

    PubMed Central

    Xu, Feng; Helfen, Lukas; Suhonen, Heikki; Elgrabli, Dan; Bayat, Sam; Reischig, Péter; Baumbach, Tilo; Cloetens, Peter

    2012-01-01

    Structure and composition at the nanoscale determine the behavior of biological systems and engineered materials. The drive to understand and control this behavior has placed strong demands on developing methods for high resolution imaging. In general, the improvement of three-dimensional (3D) resolution is accomplished by tightening constraints: reduced manageable specimen sizes, decreasing analyzable volumes, degrading contrasts, and increasing sample preparation efforts. Aiming to overcome these limitations, we present a non-destructive and multiple-contrast imaging technique, using principles of X-ray laminography, thus generalizing tomography towards laterally extended objects. We retain advantages that are usually restricted to 2D microscopic imaging, such as scanning of large areas and subsequent zooming-in towards a region of interest at the highest possible resolution. Our technique permits correlating the 3D structure and the elemental distribution yielding a high sensitivity to variations of the electron density via coherent imaging and to local trace element quantification through X-ray fluorescence. We demonstrate the method by imaging a lithographic nanostructure and an aluminum alloy. Analyzing a biological system, we visualize in lung tissue the subcellular response to toxic stress after exposure to nanotubes. We show that most of the nanotubes are trapped inside alveolar macrophages, while a small portion of the nanotubes has crossed the barrier to the cellular space of the alveolar wall. In general, our method is non-destructive and can be combined with different sample environmental or loading conditions. We therefore anticipate that correlative X-ray nano-laminography will enable a variety of in situ and in operando 3D studies. PMID:23185554

  7. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours.

    PubMed

    Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

    2012-08-01

    Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: first, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction-this not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide

  8. Field of Attention for Instantaneous Object Recognition

    PubMed Central

    Yao, Jian-Gao; Gao, Xin; Yan, Hong-Mei; Li, Chao-Yi

    2011-01-01

    Background Instantaneous object discrimination and categorization are fundamental cognitive capacities performed with the guidance of visual attention. Visual attention enables selection of a salient object within a limited area of the visual field; we referred to as “field of attention” (FA). Though there is some evidence concerning the spatial extent of object recognition, the following questions still remain unknown: (a) how large is the FA for rapid object categorization, (b) how accuracy of attention is distributed over the FA, and (c) how fast complex objects can be categorized when presented against backgrounds formed by natural scenes. Methodology/Principal Findings To answer these questions, we used a visual perceptual task in which subjects were asked to focus their attention on a point while being required to categorize briefly flashed (20 ms) photographs of natural scenes by indicating whether or not these contained an animal. By measuring the accuracy of categorization at different eccentricities from the fixation point, we were able to determine the spatial extent and the distribution of accuracy over the FA, as well as the speed of categorizing objects using stimulus onset asynchrony (SOA). Our results revealed that subjects are able to rapidly categorize complex natural images within about 0.1 s without eye movement, and showed that the FA for instantaneous image categorization covers a visual field extending 20°×24°, and accuracy was highest (>90%) at the center of FA and declined with increasing eccentricity. Conclusions/Significance In conclusion, human beings are able to categorize complex natural images at a glance over a large extent of the visual field without eye movement. PMID:21283690

  9. Performance analysis of different surface reconstruction algorithms for 3D reconstruction of outdoor objects from their digital images.

    PubMed

    Maiti, Abhik; Chakravarty, Debashish

    2016-01-01

    3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality. PMID:27386376

  10. Recovery of 3D volume from 2-tone images of novel objects.

    PubMed

    Moore, C; Cavanagh, P

    1998-07-01

    In 2-tone images (e.g., Dallenbach's cow), only two levels of brightness are used to convey image structure-dark object regions and shadows are turned to black and light regions are light regions are turned white. Despite a lack of shading, hue and texture information, many 2-tone images of familiar objects and scenes are accurately interpreted, even by naive observers. Objects frequently appear fully volumetric and are distinct from their shadows. If perceptual interpretation of 2-tone images is accomplished via bottom-up processes on the basis of geometrical structure projected to the image (e.g., volumetric parts, contour and junction information) novel objects should appear volumetric as readily as their familiar counterparts. We demonstrate that accurate volumetric representations are rarely extracted from 2-tone images of novel objects, even when these objects are constructed from volumetric primitives such as generalized cones (Marr, D., Nishihara, H.K., 1978. Proceedings of the Royal Society London 200, 269-294; Biederman, I. 1985. Computer Vision, Graphics, and Image Processing 32, 29-73), or from the rearranged components of a familiar object which is itself recognizable as a 2-tone image. Even familiar volumes such as canonical bricks and cylinders require scenes with redundant structure (e.g., rows of cylinders) or explicit lighting (a lamp in the image) for recovery of global volumetric shape. We conclude that 2-tone image perception is not mediated by bottom-up extraction of geometrical features such as junctions or volumetric parts, but may rely on previously stored representations in memory and a model of the illumination of the scene. The success of this top-down strategy implies it is available for general object recognition in natural scenes. PMID:9735536

  11. A contest of sensors in close range 3D imaging: performance evaluation with a new metric test object

    NASA Astrophysics Data System (ADS)

    Hess, M.; Robson, S.; Hosseininaveh Ahmadabadian, A.

    2014-06-01

    An independent means of 3D image quality assessment is introduced, addressing non-professional users of sensors and freeware, which is largely characterized as closed-sourced and by the absence of quality metrics for processing steps, such as alignment. A performance evaluation of commercially available, state-of-the-art close range 3D imaging technologies is demonstrated with the help of a newly developed Portable Metric Test Artefact. The use of this test object provides quality control by a quantitative assessment of 3D imaging sensors. It will enable users to give precise specifications which spatial resolution and geometry recording they expect as outcome from their 3D digitizing process. This will lead to the creation of high-quality 3D digital surrogates and 3D digital assets. The paper is presented in the form of a competition of teams, and a possible winner will emerge.

  12. The role of the foreshortening cue in the perception of 3D object slant.

    PubMed

    Ivanov, Iliya V; Kramer, Daniel J; Mullen, Kathy T

    2014-01-01

    Slant is the degree to which a surface recedes or slopes away from the observer about the horizontal axis. The perception of surface slant may be derived from static monocular cues, including linear perspective and foreshortening, applied to single shapes or to multi-element textures. It is still unclear the extent to which color vision can use these cues to determine slant in the absence of achromatic contrast. Although previous demonstrations have shown that some pictures and images may lose their depth when presented at isoluminance, this has not been tested systematically using stimuli within the spatio-temporal passband of color vision. Here we test whether the foreshortening cue from surface compression (change in the ratio of width to length) can induce slant perception for single shapes for both color and luminance vision. We use radial frequency patterns with narrowband spatio-temporal properties. In the first experiment, both a manual task (lever rotation) and a visual task (line rotation) are used as metrics to measure the perception of slant for achromatic, red-green isoluminant and S-cone isolating stimuli. In the second experiment, we measure slant discrimination thresholds as a function of depicted slant in a 2AFC paradigm and find similar thresholds for chromatic and achromatic stimuli. We conclude that both color and luminance vision can use the foreshortening of a single surface to perceive slant, with performances similar to those obtained using other strong cues for slant, such as texture. This has implications for the role of color in monocular 3D vision, and the cortical organization used in 3D object perception. PMID:24216007

  13. Detection of hidden objects using a real-time 3-D millimeter-wave imaging system

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon, Avihai; Levanon, Assaf; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, N. S.

    2014-10-01

    Millimeter (mm)and sub-mm wavelengths or terahertz (THz) band have several properties that motivate their use in imaging for security applications such as recognition of hidden objects, dangerous materials, aerosols, imaging through walls as in hostage situations, and also in bad weather conditions. There is no known ionization hazard for biological tissue, and atmospheric degradation of THz radiation is relatively low for practical imaging distances. We recently developed a new technology for the detection of THz radiation. This technology is based on very inexpensive plasma neon indicator lamps, also known as Glow Discharge Detector (GDD), that can be used as very sensitive THz radiation detectors. Using them, we designed and constructed a Focal Plane Array (FPA) and obtained recognizable2-dimensional THz images of both dielectric and metallic objects. Using THz wave it is shown here that even concealed weapons made of dielectric material can be detected. An example is an image of a knife concealed inside a leather bag and also under heavy clothing. Three-dimensional imaging using radar methods can enhance those images since it can allow the isolation of the concealed objects from the body and environmental clutter such as nearby furniture or other people. The GDDs enable direct heterodyning between the electric field of the target signal and the reference signal eliminating the requirement for expensive mixers, sources, and Low Noise Amplifiers (LNAs).We expanded the ability of the FPA so that we are able to obtain recognizable 2-dimensional THz images in real time. We show here that the THz detection of objects in three dimensions, using FMCW principles is also applicable in real time. This imaging system is also shown here to be capable of imaging objects from distances allowing standoff detection of suspicious objects and humans from large distances.

  14. 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

  15. An objective method for 3D quality prediction using visual annoyance and acceptability level

    NASA Astrophysics Data System (ADS)

    Khaustova, Darya; Fournier, Jérôme; Wyckens, Emmanuel; Le Meur, Olivier

    2015-03-01

    This study proposes a new objective metric for video quality assessment. It predicts the impact of technical quality parameters relevant to visual discomfort on human perception. The proposed metric is based on a 3-level color scale: (1) Green - not annoying, (2) Orange - annoying but acceptable, (3) Red - not acceptable. Therefore, each color category reflects viewers' judgment based on stimulus acceptability and induced visual annoyance. The boundary between the "Green" and "Orange" categories defines the visual annoyance threshold, while the boundary between the "Orange" and "Red" categories defines the acceptability threshold. Once the technical quality parameters are measured, they are compared to perceptual thresholds. Such comparison allows estimating the quality of the 3D video sequence. Besides, the proposed metric is adjustable to service or production requirements by changing the percentage of acceptability and/or visual annoyance. The performance of the metric is evaluated in a subjective experiment that uses three stereoscopic scenes. Five view asymmetries with four degradation levels were introduced into initial test content. The results demonstrate high correlations between subjective scores and objective predictions for all view asymmetries.

  16. Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

    NASA Astrophysics Data System (ADS)

    Yu, Qian; Helmholz, Petra; Belton, David

    2016-06-01

    In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.

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

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.

    1988-02-01

    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. 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.

  19. Software for Building Models of 3D Objects via the Internet

    NASA Technical Reports Server (NTRS)

    Schramer, Tim; Jensen, Jeff

    2003-01-01

    The Virtual EDF Builder (where EDF signifies Electronic Development Fixture) is a computer program that facilitates the use of the Internet for building and displaying digital models of three-dimensional (3D) objects that ordinarily comprise assemblies of solid models created previously by use of computer-aided-design (CAD) programs. The Virtual EDF Builder resides on a Unix-based server computer. It is used in conjunction with a commercially available Web-based plug-in viewer program that runs on a client computer. The Virtual EDF Builder acts as a translator between the viewer program and a database stored on the server. The translation function includes the provision of uniform resource locator (URL) links to other Web-based computer systems and databases. The Virtual EDF builder can be used in two ways: (1) If the client computer is Unix-based, then it can assemble a model locally; the computational load is transferred from the server to the client computer. (2) Alternatively, the server can be made to build the model, in which case the server bears the computational load and the results are downloaded to the client computer or workstation upon completion.

  20. A multi-objective optimization framework to model 3D river and landscape evolution processes

    NASA Astrophysics Data System (ADS)

    Bizzi, Simone; Castelletti, Andrea; Cominola, Andrea; Mason, Emanuele; Paik, Kyungrock

    2013-04-01

    Water and sediment interactions shape hillslopes, regulate soil erosion and sedimentation, and organize river networks. Landscape evolution and river organization occur at various spatial and temporal scale and the understanding and modelling of them is highly complex. The idea of a least action principle governing river networks evolution has been proposed many times as a simpler approach among the ones existing in the literature. These theories assume that river networks, as observed in nature, self-organize and act on soil transportation in order to satisfy a particular "optimality" criterion. Accordingly, river and landscape weathering can be simulated by solving an optimization problem, where the choice of the criterion to be optimized becomes the initial assumption. The comparison between natural river networks and optimized ones verifies the correctness of this initial assumption. Yet, various criteria have been proposed in literature and there is no consensus on which is better able to explain river network features observed in nature like network branching and river bed profile: each one is able to reproduce some river features through simplified modelling of the natural processes, but it fails to characterize the whole complexity (3D and its dynamic) of the natural processes. Some of the criteria formulated in the literature partly conflict: the reason is that their formulation rely on mathematical and theoretical simplifications of the natural system that are suitable for specific spatial and temporal scale but fails to represent the whole processes characterizing landscape evolution. In an attempt to address some of these scientific questions, we tested the suitability of using a multi-objective optimization framework to describe river and landscape evolution in a 3D spatial domain. A synthetic landscape is used to this purpose. Multiple, alternative river network evolutions, corresponding to as many tradeoffs between the different and partly

  1. Ionized Outflows in 3-D Insights from Herbig-Haro Objects and Applications to Nearby AGN

    NASA Technical Reports Server (NTRS)

    Cecil, Gerald

    1999-01-01

    HST shows that the gas distributions of these objects are complex and clump at the limit of resolution. HST spectra have lumpy emission-line profiles, indicating unresolved sub-structure. The advantages of 3D over slits on gas so distributed are: robust flux estimates of various dynamical systems projected along lines of sight, sensitivity to fainter spectral lines that are physical diagnostics (reddening-gas density, T, excitation mechanisms, abundances), and improved prospects for recovery of unobserved dimensions of phase-space. These advantages al- low more confident modeling for more profound inquiry into underlying dynamics. The main complication is the effort required to link multi- frequency datasets that optimally track the energy flow through various phases of the ISM. This tedium has limited the number of objects that have been thoroughly analyzed to the a priori most spectacular systems. For HHO'S, proper-motions constrain the ambient B-field, shock velocity, gas abundances, mass-loss rates, source duty-cycle, and tie-ins with molecular flows. If the shock speed, hence ionization fraction, is indeed small then the ionized gas is a significant part of the flow energetics. For AGN'S, nuclear beaming is a source of ionization ambiguity. Establishing the energetics of the outflow is critical to determining how the accretion disk loses its energy. CXO will provide new constraints (especially spectral) on AGN outflows, and STIS UV-spectroscopy is also constraining cloud properties (although limited by extinction). HHO's show some of the things that we will find around AGN'S. I illustrate these points with results from ground-based and HST programs being pursued with collaborators.

  2. Quantitative analysis and feature recognition in 3-D microstructural data sets

    NASA Astrophysics Data System (ADS)

    Lewis, A. C.; Suh, C.; Stukowski, M.; Geltmacher, A. B.; Spanos, G.; Rajan, K.

    2006-12-01

    A three-dimensional (3-D) reconstruction of an austenitic stainless-steel microstructure was used as input for an image-based finite-element model to simulate the anisotropic elastic mechanical response of the microstructure. The quantitative data-mining and data-warehousing techniques used to correlate regions of high stress with critical microstructural features are discussed. Initial analysis of elastic stresses near grain boundaries due to mechanical loading revealed low overall correlation with their location in the microstructure. However, the use of data-mining and feature-tracking techniques to identify high-stress outliers revealed that many of these high-stress points are generated near grain boundaries and grain edges (triple junctions). These techniques also allowed for the differentiation between high stresses due to boundary conditions of the finite volume reconstructed, and those due to 3-D microstructural features.

  3. New 3D thermal evolution model for icy bodies application to trans-Neptunian objects

    NASA Astrophysics Data System (ADS)

    Guilbert-Lepoutre, A.; Lasue, J.; Federico, C.; Coradini, A.; Orosei, R.; Rosenberg, E. D.

    2011-05-01

    Context. Thermal evolution models have been developed over the years to investigate the evolution of thermal properties based on the transfer of heat fluxes or transport of gas through a porous matrix, among others. Applications of such models to trans-Neptunian objects (TNOs) and Centaurs has shown that these bodies could be strongly differentiated from the point of view of chemistry (i.e. loss of most volatile ices), as well as from physics (e.g. melting of water ice), resulting in stratified internal structures with differentiated cores and potential pristine material close to the surface. In this context, some observational results, such as the detection of crystalline water ice or volatiles, remain puzzling. Aims: In this paper, we would like to present a new fully three-dimensional thermal evolution model. With this model, we aim to improve determination of the temperature distribution inside icy bodies such as TNOs by accounting for lateral heat fluxes, which have been proven to be important for accurate simulations. We also would like to be able to account for heterogeneous boundary conditions at the surface through various albedo properties, for example, that might induce different local temperature distributions. Methods: In a departure from published modeling approaches, the heat diffusion problem and its boundary conditions are represented in terms of real spherical harmonics, increasing the numerical efficiency by roughly an order of magnitude. We then compare this new model and another 3D model recently published to illustrate the advantages and limits of the new model. We try to put some constraints on the presence of crystalline water ice at the surface of TNOs. Results: The results obtained with this new model are in excellent agreement with results obtained by different groups with various models. Small TNOs could remain primitive unless they are formed quickly (less than 2 Myr) or are debris from the disruption of larger bodies. We find that, for

  4. 3D models automatic reconstruction of selected close range objects. (Polish Title: Automatyczna rekonstrukcja modeli 3D małych obiektów bliskiego zasiegu)

    NASA Astrophysics Data System (ADS)

    Zaweiska, D.

    2013-12-01

    Reconstruction of three-dimensional, realistic models of objects from digital images has been the topic of research in many areas of science for many years. This development is stimulated by new technologies and tools, which appeared recently, such as digital photography, laser scanners, increase in the equipment efficiency and Internet. The objective of this paper is to present results of automatic modeling of selected close range objects, with the use of digital photographs acquired by the Hasselblad H4D50 camera. The author's software tool was utilized for calculations; it performs successive stages of the 3D model creation. The modeling process was presented as the complete process which starts from acquisition of images and which is completed by creation of a photorealistic 3D model in the same software environment. Experiments were performed for selected close range objects, with appropriately arranged image geometry, creating a ring around the measured object. The Area Base Matching (CC/LSM) method, the RANSAC algorithm, with the use of tensor calculus, were utilized form automatic matching of points detected with the SUSAN algorithm. Reconstruction of the surface of model generation is one of the important stages of 3D modeling. Reconstruction of precise surfaces, performed on the basis of a non-organized cloud of points, acquired from automatic processing of digital images, is a difficult task, which has not been finally solved. Creation of poly-angular models, which may meet high requirements concerning modeling and visualization is required in many applications. The polynomial method is usually the best way to precise representation of measurement results, and, at the same time, to achieving the optimum description of the surface. Three algorithm were tested: the volumetric method (VCG), the Poisson method and the Ball pivoting method. Those methods are mostly applied to modeling of uniform grids of points. Results of experiments proved that incorrect

  5. True-3D Accentuating of Grids and Streets in Urban Topographic Maps Enhances Human Object Location Memory

    PubMed Central

    Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

    2015-01-01

    Cognitive representations of learned map information are subject to systematic distortion errors. Map elements that divide a map surface into regions, such as content-related linear symbols (e.g. streets, rivers, railway systems) or additional artificial layers (coordinate grids), provide an orientation pattern that can help users to reduce distortions in their mental representations. In recent years, the television industry has started to establish True-3D (autostereoscopic) displays as mass media. These modern displays make it possible to watch dynamic and static images including depth illusions without additional devices, such as 3D glasses. In these images, visual details can be distributed over different positions along the depth axis. Some empirical studies of vision research provided first evidence that 3D stereoscopic content attracts higher attention and is processed faster. So far, the impact of True-3D accentuating has not yet been explored concerning spatial memory tasks and cartography. This paper reports the results of two empirical studies that focus on investigations whether True-3D accentuating of artificial, regular overlaying line features (i.e. grids) and content-related, irregular line features (i.e. highways and main streets) in official urban topographic maps (scale 1/10,000) further improves human object location memory performance. The memory performance is measured as both the percentage of correctly recalled object locations (hit rate) and the mean distances of correctly recalled objects (spatial accuracy). It is shown that the True-3D accentuating of grids (depth offset: 5 cm) significantly enhances the spatial accuracy of recalled map object locations, whereas the True-3D emphasis of streets significantly improves the hit rate of recalled map object locations. These results show the potential of True-3D displays for an improvement of the cognitive representation of learned cartographic information. PMID:25679208

  6. True-3D accentuating of grids and streets in urban topographic maps enhances human object location memory.

    PubMed

    Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

    2015-01-01

    Cognitive representations of learned map information are subject to systematic distortion errors. Map elements that divide a map surface into regions, such as content-related linear symbols (e.g. streets, rivers, railway systems) or additional artificial layers (coordinate grids), provide an orientation pattern that can help users to reduce distortions in their mental representations. In recent years, the television industry has started to establish True-3D (autostereoscopic) displays as mass media. These modern displays make it possible to watch dynamic and static images including depth illusions without additional devices, such as 3D glasses. In these images, visual details can be distributed over different positions along the depth axis. Some empirical studies of vision research provided first evidence that 3D stereoscopic content attracts higher attention and is processed faster. So far, the impact of True-3D accentuating has not yet been explored concerning spatial memory tasks and cartography. This paper reports the results of two empirical studies that focus on investigations whether True-3D accentuating of artificial, regular overlaying line features (i.e. grids) and content-related, irregular line features (i.e. highways and main streets) in official urban topographic maps (scale 1/10,000) further improves human object location memory performance. The memory performance is measured as both the percentage of correctly recalled object locations (hit rate) and the mean distances of correctly recalled objects (spatial accuracy). It is shown that the True-3D accentuating of grids (depth offset: 5 cm) significantly enhances the spatial accuracy of recalled map object locations, whereas the True-3D emphasis of streets significantly improves the hit rate of recalled map object locations. These results show the potential of True-3D displays for an improvement of the cognitive representation of learned cartographic information. PMID:25679208

  7. Laser Transfer of Metals and Metal Alloys for Digital Microfabrication of 3D Objects.

    PubMed

    Zenou, Michael; Sa'ar, Amir; Kotler, Zvi

    2015-09-01

    3D copper logos printed on epoxy glass laminates are demonstrated. The structures are printed using laser transfer of molten metal microdroplets. The example in the image shows letters of 50 µm width, with each letter being taller than the last, from a height of 40 µm ('s') to 190 µm ('l'). The scanning microscopy image is taken at a tilt, and the topographic image was taken using interferometric 3D microscopy, to show the effective control of this technique. PMID:25966320

  8. The effect of object speed and direction on the performance of 3D speckle tracking using a 3D swept-volume ultrasound probe

    NASA Astrophysics Data System (ADS)

    Harris, Emma J.; Miller, Naomi R.; Bamber, Jeffrey C.; Symonds-Tayler, J. Richard N.; Evans, Philip M.

    2011-11-01

    Three-dimensional (3D) soft tissue tracking using 3D ultrasound is of interest for monitoring organ motion during therapy. Previously we demonstrated feature tracking of respiration-induced liver motion in vivo using a 3D swept-volume ultrasound probe. The aim of this study was to investigate how object speed affects the accuracy of tracking ultrasonic speckle in the absence of any structural information, which mimics the situation in homogenous tissue for motion in the azimuthal and elevational directions. For object motion prograde and retrograde to the sweep direction of the transducer, the spatial sampling frequency increases or decreases with object speed, respectively. We examined the effect object motion direction of the transducer on tracking accuracy. We imaged a homogenous ultrasound speckle phantom whilst moving the probe with linear motion at a speed of 0-35 mm s-1. Tracking accuracy and precision were investigated as a function of speed, depth and direction of motion for fixed displacements of 2 and 4 mm. For the azimuthal direction, accuracy was better than 0.1 and 0.15 mm for displacements of 2 and 4 mm, respectively. For a 2 mm displacement in the elevational direction, accuracy was better than 0.5 mm for most speeds. For 4 mm elevational displacement with retrograde motion, accuracy and precision reduced with speed and tracking failure was observed at speeds of greater than 14 mm s-1. Tracking failure was attributed to speckle de-correlation as a result of decreasing spatial sampling frequency with increasing speed of retrograde motion. For prograde motion, tracking failure was not observed. For inter-volume displacements greater than 2 mm, only prograde motion should be tracked which will decrease temporal resolution by a factor of 2. Tracking errors of the order of 0.5 mm for prograde motion in the elevational direction indicates that using the swept probe technology speckle tracking accuracy is currently too poor to track homogenous tissue over

  9. Affective SSVEP BCI to effectively control 3D objects by using a prism array-based display

    NASA Astrophysics Data System (ADS)

    Mun, Sungchul; Park, Min-Chul

    2014-06-01

    3D objects with depth information can provide many benefits to users in education, surgery, and interactions. In particular, many studies have been done to enhance sense of reality in 3D interaction. Viewing and controlling stereoscopic 3D objects with crossed or uncrossed disparities, however, can cause visual fatigue due to the vergenceaccommodation conflict generally accepted in 3D research fields. In order to avoid the vergence-accommodation mismatch and provide a strong sense of presence to users, we apply a prism array-based display to presenting 3D objects. Emotional pictures were used as visual stimuli in control panels to increase information transfer rate and reduce false positives in controlling 3D objects. Involuntarily motivated selective attention by affective mechanism can enhance steady-state visually evoked potential (SSVEP) amplitude and lead to increased interaction efficiency. More attentional resources are allocated to affective pictures with high valence and arousal levels than to normal visual stimuli such as white-and-black oscillating squares and checkerboards. Among representative BCI control components (i.e., eventrelated potentials (ERP), event-related (de)synchronization (ERD/ERS), and SSVEP), SSVEP-based BCI was chosen in the following reasons. It shows high information transfer rates and takes a few minutes for users to control BCI system while few electrodes are required for obtaining reliable brainwave signals enough to capture users' intention. The proposed BCI methods are expected to enhance sense of reality in 3D space without causing critical visual fatigue to occur. In addition, people who are very susceptible to (auto) stereoscopic 3D may be able to use the affective BCI.

  10. Visualizing 3D Objects from 2D Cross Sectional Images Displayed "In-Situ" versus "Ex-Situ"

    ERIC Educational Resources Information Center

    Wu, Bing; Klatzky, Roberta L.; Stetten, George

    2010-01-01

    The present research investigates how mental visualization of a 3D object from 2D cross sectional images is influenced by displacing the images from the source object, as is customary in medical imaging. Three experiments were conducted to assess people's ability to integrate spatial information over a series of cross sectional images in order to…

  11. 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. PMID:24808564

  12. The 3-D image recognition based on fuzzy neural network technology

    NASA Technical Reports Server (NTRS)

    Hirota, Kaoru; Yamauchi, Kenichi; Murakami, Jun; Tanaka, Kei

    1993-01-01

    Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented.

  13. Genome-Wide Identification and 3D Modeling of Proteins involved in DNA Damage Recognition and Repair (Final Report)

    SciTech Connect

    Abagyan, Ruben; An, Jianghong

    2005-08-12

    DNA Damage Recognition and Repair (DDR&R) proteins play a critical role in cellular responses to low-dose radiation and are associated with cancer. We have performed a systematic, genome-wide computational analysis of genomic data for human genes involved in the DDR&R process. The significant achievements of this project include: 1) Construction of the computational pipeline for searching DDR&R genes, building and validation of 3D models of proteins involved in DDR&R; 2) Functional and structural annotation of the 3D models and generation of comprehensive lists of suggested knock-out mutations; and the development of a method to predict the effects of mutations. Large scale testing of technology to identify novel small binding pockets in protein structures leading to new DDRR inhibitor strategies 3) Improvements of macromolecular docking technology (see the CAPRI 1-3 and 4-5 results) 4) Development of a new algorithm for improved analysis of high-density oligonucleotide arrays for gene expression profiling; 5) Construction and maintenance of the DNA Damage Recognition and Repair Database; 6) Producing 15 research papers (12 published and 3 in preparation).

  14. Genome-Wide Identification and 3D Modeling of Proteins involved in DNA Damage Recognition and Repair (Final Report)

    SciTech Connect

    Ruben A. Abagyan, PhD

    2004-04-15

    OAK-B135 DNA Damage Recognition and Repair (DDR and R) proteins play a critical role in cellular responses to low-dose radiation and are associated with cancer. the authors have performed a systematic, genome-wide computational analysis of genomic data for human genes involved in the DDR and R process. The significant achievements of this project include: (1) Construction of the computational pipeline for searching DDR and R genes, building and validation of 3D models of proteins involved in DDR and R; (2) Functional and structural annotation of the 3D models and generation of comprehensive lists of suggested knock-out mutations; (3) Important improvement of macromolecular docking technology and its application to predict the DNA-Protein complex conformation; (4) Development of a new algorithm for improved analysis of high-density oligonucleotide arrays for gene expression profiling; (5) Construction and maintenance of the DNA Damage Recognition and Repair Database; and (6) Producing 14 research papers (10 published and 4 in preparation).

  15. An Efficient Bayesian Approach to Exploit the Context of Object-Action Interaction for Object Recognition

    PubMed Central

    Yoon, Sungbaek; Park, Hyunjin; Yi, Juneho

    2016-01-01

    This research features object recognition that exploits the context of object-action interaction to enhance the recognition performance. Since objects have specific usages, and human actions corresponding to these usages can be associated with these objects, human actions can provide effective information for object recognition. When objects from different categories have similar appearances, the human action associated with each object can be very effective in resolving ambiguities related to recognizing these objects. We propose an efficient method that integrates human interaction with objects into a form of object recognition. We represent human actions by concatenating poselet vectors computed from key frames and learn the probabilities of objects and actions using random forest and multi-class AdaBoost algorithms. Our experimental results show that poselet representation of human actions is quite effective in integrating human action information into object recognition. PMID:27347977

  16. An Efficient Bayesian Approach to Exploit the Context of Object-Action Interaction for Object Recognition.

    PubMed

    Yoon, Sungbaek; Park, Hyunjin; Yi, Juneho

    2016-01-01

    This research features object recognition that exploits the context of object-action interaction to enhance the recognition performance. Since objects have specific usages, and human actions corresponding to these usages can be associated with these objects, human actions can provide effective information for object recognition. When objects from different categories have similar appearances, the human action associated with each object can be very effective in resolving ambiguities related to recognizing these objects. We propose an efficient method that integrates human interaction with objects into a form of object recognition. We represent human actions by concatenating poselet vectors computed from key frames and learn the probabilities of objects and actions using random forest and multi-class AdaBoost algorithms. Our experimental results show that poselet representation of human actions is quite effective in integrating human action information into object recognition. PMID:27347977

  17. Model attraction in medical image object recognition

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Zingaretti, Primo

    1995-04-01

    This paper presents as new approach to image recognition based on a general attraction principle. A cognitive recognition is governed by a 'focus on attention' process that concentrates on the visual data subset of task- relevant type only. Our model-based approach combines it with another process, focus on attraction, which concentrates on the transformations of visual data having relevance for the matching. The recognition process is characterized by an intentional evolution of the visual data. This chain of image transformations is viewed as driven by an attraction field that attempts to reduce the distance between the image-point and the model-point in the feature space. The field sources are determined during a learning phase, by supplying the system with a training set. The paper describes a medical interpretation case in the feature space, concerning human skin lesions. The samples of the training set, supplied by the dermatologists, allow the system to learn models of lesions in terms of features such as hue factor, asymmetry factor, and asperity factor. The comparison of the visual data with the model derives the trend of image transformations, allowing a better definition of the given image and its classification. The algorithms are implemented in C language on a PC equipped with Matrox Image Series IM-1280 acquisition and processing boards. The work is now in progress.

  18. 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…

  19. The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

    NASA Technical Reports Server (NTRS)

    Maluf, David A.; Cheeseman, Peter; Smelyanskyi, Vadim N.; Kuehnel, Frank; Morris, Robin D.; Norvig, Peter (Technical Monitor)

    2001-01-01

    This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

  20. Simulated and Real Sheet-of-Light 3D Object Scanning Using a-Si:H Thin Film PSD Arrays

    PubMed Central

    Contreras, Javier; Tornero, Josep; Ferreira, Isabel; Martins, Rodrigo; Gomes, Luis; Fortunato, Elvira

    2015-01-01

    A MATLAB/SIMULINK software simulation model (structure and component blocks) has been constructed in order to view and analyze the potential of the PSD (Position Sensitive Detector) array concept technology before it is further expanded or developed. This simulation allows changing most of its parameters, such as the number of elements in the PSD array, the direction of vision, the viewing/scanning angle, the object rotation, translation, sample/scan/simulation time, etc. In addition, results show for the first time the possibility of scanning an object in 3D when using an a-Si:H thin film 128 PSD array sensor and hardware/software system. Moreover, this sensor technology is able to perform these scans and render 3D objects at high speeds and high resolutions when using a sheet-of-light laser within a triangulation platform. As shown by the simulation, a substantial enhancement in 3D object profile image quality and realism can be achieved by increasing the number of elements of the PSD array sensor as well as by achieving an optimal position response from the sensor since clearly the definition of the 3D object profile depends on the correct and accurate position response of each detector as well as on the size of the PSD array. PMID:26633403

  1. Simulated and Real Sheet-of-Light 3D Object Scanning Using a-Si:H Thin Film PSD Arrays.

    PubMed

    Contreras, Javier; Tornero, Josep; Ferreira, Isabel; Martins, Rodrigo; Gomes, Luis; Fortunato, Elvira

    2015-01-01

    A MATLAB/SIMULINK software simulation model (structure and component blocks) has been constructed in order to view and analyze the potential of the PSD (Position Sensitive Detector) array concept technology before it is further expanded or developed. This simulation allows changing most of its parameters, such as the number of elements in the PSD array, the direction of vision, the viewing/scanning angle, the object rotation, translation, sample/scan/simulation time, etc. In addition, results show for the first time the possibility of scanning an object in 3D when using an a-Si:H thin film 128 PSD array sensor and hardware/software system. Moreover, this sensor technology is able to perform these scans and render 3D objects at high speeds and high resolutions when using a sheet-of-light laser within a triangulation platform. As shown by the simulation, a substantial enhancement in 3D object profile image quality and realism can be achieved by increasing the number of elements of the PSD array sensor as well as by achieving an optimal position response from the sensor since clearly the definition of the 3D object profile depends on the correct and accurate position response of each detector as well as on the size of the PSD array. PMID:26633403

  2. 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

  3. Possibility of object recognition using Altera's model based design approach

    NASA Astrophysics Data System (ADS)

    Tickle, A. J.; Wu, F.; Harvey, P. K.; Smith, J. S.

    2009-07-01

    Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.

  4. Infants' Recognition of Objects Using Canonical Color

    ERIC Educational Resources Information Center

    Kimura, Atsushi; Wada, Yuji; Yang, Jiale; Otsuka, Yumiko; Dan, Ippeita; Masuda, Tomohiro; Kanazawa, So; Yamaguchi, Masami K.

    2010-01-01

    We explored infants' ability to recognize the canonical colors of daily objects, including two color-specific objects (human face and fruit) and a non-color-specific object (flower), by using a preferential looking technique. A total of 58 infants between 5 and 8 months of age were tested with a stimulus composed of two color pictures of an object…

  5. A Comparative Analysis between Active and Passive Techniques for Underwater 3D Reconstruction of Close-Range Objects

    PubMed Central

    Bianco, Gianfranco; Gallo, Alessandro; Bruno, Fabio; Muzzupappa, Maurizio

    2013-01-01

    In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms. PMID:23966193

  6. A comparative analysis between active and passive techniques for underwater 3D reconstruction of close-range objects.

    PubMed

    Bianco, Gianfranco; Gallo, Alessandro; Bruno, Fabio; Muzzupappa, Maurizio

    2013-01-01

    In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms. PMID:23966193

  7. Method of synthesized phase objects for pattern recognition: matched filtering.

    PubMed

    Yezhov, Pavel V; Kuzmenko, Alexander V; Kim, Jin-Tae; Smirnova, Tatiana N

    2012-12-31

    To solve the pattern recognition problem, a method of synthesized phase objects is suggested. The essence of the suggested method is that synthesized phase objects are used instead of real amplitude objects. The former is object-dependent phase distributions calculated using the iterative Fourier-transform (IFT) algorithm. The method is experimentally studied with a Vander Lugt optical-digital 4F-correlator. We present the comparative analysis of recognition results using conventional and proposed methods, estimate the sensitivity of the latter to distortions of the structure of objects, and determine the applicability limits. It is demonstrated that the proposed method allows one: (а) to simplify the procedure of choice of recognition signs (criteria); (b) to obtain one-type δ-like recognition signals irrespective of the type of objects; (с) to improve signal-to-noise ratio (SNR) for correlation signals by 20 - 30 dB on average. The spatial separation of the Fourier-spectra of objects and optical noises of the correlator by means of the superposition of the phase grating on recognition objects at the recording of holographic filters and at the matched filtering has additionally improved SNR (>10 dB) for correlation signals. To introduce recognition objects in the correlator, we use a SLM LC-R 2500 device. Matched filters are recorded on a self-developing photopolymer. PMID:23388812

  8. Development of 3D interactive visual objects using the Scripps Institution of Oceanography's Visualization Center

    NASA Astrophysics Data System (ADS)

    Kilb, D.; Reif, C.; Peach, C.; Keen, C. S.; Smith, B.; Mellors, R. J.

    2003-12-01

    Within the last year scientists and educators at the Scripps Institution of Oceanography (SIO), the Birch Aquarium at Scripps and San Diego State University have collaborated with education specialists to develop 3D interactive graphic teaching modules for use in the classroom and in teacher workshops at the SIO Visualization center (http://siovizcenter.ucsd.edu). The unique aspect of the SIO Visualization center is that the center is designed around a 120 degree curved Panoram floor-to-ceiling screen (8'6" by 28'4") that immerses viewers in a virtual environment. The center is powered by an SGI 3400 Onyx computer that is more powerful, by an order of magnitude in both speed and memory, than typical base systems currently used for education and outreach presentations. This technology allows us to display multiple 3D data layers (e.g., seismicity, high resolution topography, seismic reflectivity, draped interferometric synthetic aperture radar (InSAR) images, etc.) simultaneously, render them in 3D stereo, and take a virtual flight through the data as dictated on the spot by the user. This system can also render snapshots, images and movies that are too big for other systems, and then export smaller size end-products to more commonly used computer systems. Since early 2002, we have explored various ways to provide informal education and outreach focusing on current research presented directly by the researchers doing the work. The Center currently provides a centerpiece for instruction on southern California seismology for K-12 students and teachers for various Scripps education endeavors. Future plans are in place to use the Visualization Center at Scripps for extended K-12 and college educational programs. In particular, we will be identifying K-12 curriculum needs, assisting with teacher education, developing assessments of our programs and products, producing web-accessible teaching modules and facilitating the development of appropriate teaching tools to be

  9. Automatic Recognition of Object Names in Literature

    NASA Astrophysics Data System (ADS)

    Bonnin, C.; Lesteven, S.; Derriere, S.; Oberto, A.

    2008-08-01

    SIMBAD is a database of astronomical objects that provides (among other things) their bibliographic references in a large number of journals. Currently, these references have to be entered manually by librarians who read each paper. To cope with the increasing number of papers, CDS develops a tool to assist the librarians in their work, taking advantage of the Dictionary of Nomenclature of Celestial Objects, which keeps track of object acronyms and of their origin. The program searches for object names directly in PDF documents by comparing the words with all the formats stored in the Dictionary of Nomenclature. It also searches for variable star names based on constellation names and for a large list of usual names such as Aldebaran or the Crab. Object names found in the documents often correspond to several astronomical objects. The system retrieves all possible matches, displays them with their object type given by SIMBAD, and lets the librarian make the final choice. The bibliographic reference can then be automatically added to the object identifiers in the database. Besides, the systematic usage of the Dictionary of Nomenclature, which is updated manually, permitted to automatically check it and to detect errors and inconsistencies. Last but not least, the program collects some additional information such as the position of the object names in the document (in the title, subtitle, abstract, table, figure caption...) and their number of occurrences. In the future, this will permit to calculate the 'weight' of an object in a reference and to provide SIMBAD users with an important new information, which will help them to find the most relevant papers in the object reference list.

  10. Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

    PubMed

    Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

    2016-08-01

    Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research. PMID:26761193

  11. Flying triangulation - A motion-robust optical 3D sensor for the real-time shape acquisition of complex objects

    NASA Astrophysics Data System (ADS)

    Willomitzer, Florian; Ettl, Svenja; Arold, Oliver; Häusler, Gerd

    2013-05-01

    The three-dimensional shape acquisition of objects has become more and more important in the last years. Up to now, there are several well-established methods which already yield impressive results. However, even under quite common conditions like object movement or a complex shaping, most methods become unsatisfying. Thus, the 3D shape acquisition is still a difficult and non-trivial task. We present our measurement principle "Flying Triangulation" which enables a motion-robust 3D acquisition of complex-shaped object surfaces by a freely movable handheld sensor. Since "Flying Triangulation" is scalable, a whole sensor-zoo for different object sizes is presented. Concluding, an overview of current and future fields of investigation is given.

  12. Category-Specificity in Visual Object Recognition

    ERIC Educational Resources Information Center

    Gerlach, Christian

    2009-01-01

    Are all categories of objects recognized in the same manner visually? Evidence from neuropsychology suggests they are not: some brain damaged patients are more impaired in recognizing natural objects than artefacts whereas others show the opposite impairment. Category-effects have also been demonstrated in neurologically intact subjects, but the…

  13. Evaluation of iterative sparse object reconstruction from few projections for 3-D rotational coronary angiography.

    PubMed

    Hansis, Eberhard; Schäfer, Dirk; Dössel, Olaf; Grass, Michael

    2008-11-01

    A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the mbiL(1) norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved. PMID:18955171

  14. Eccentricity in Images of Circular and Spherical Targets and its Impact to 3D Object Reconstruction

    NASA Astrophysics Data System (ADS)

    Luhmann, T.

    2014-06-01

    This paper discusses a feature of projective geometry which causes eccentricity in the image measurement of circular and spherical targets. While it is commonly known that flat circular targets can have a significant displacement of the elliptical image centre with respect to the true imaged circle centre, it can also be shown that the a similar effect exists for spherical targets. Both types of targets are imaged with an elliptical contour. As a result, if measurement methods based on ellipses are used to detect the target (e.g. best-fit ellipses), the calculated ellipse centre does not correspond to the desired target centre in 3D space. This paper firstly discusses the use and measurement of circular and spherical targets. It then describes the geometrical projection model in order to demonstrate the eccentricity in image space. Based on numerical simulations, the eccentricity in the image is further quantified and investigated. Finally, the resulting effect in 3D space is estimated for stereo and multi-image intersections. It can be stated that the eccentricity is larger than usually assumed, and must be compensated for high-accuracy applications. Spherical targets do not show better results than circular targets. The paper is an updated version of Luhmann (2014) new experimental investigations on the effect of length measurement errors.

  15. Influence of georeference for saturated excess overland flow modelling using 3D volumetric soft geo-objects

    NASA Astrophysics Data System (ADS)

    Izham, Mohamad Yusoff; Muhamad Uznir, Ujang; Alias, Abdul Rahman; Ayob, Katimon; Wan Ruslan, Ismail

    2011-04-01

    Existing 2D data structures are often insufficient for analysing the dynamism of saturation excess overland flow (SEOF) within a basin. Moreover, all stream networks and soil surface structures in GIS must be preserved within appropriate projection plane fitting techniques known as georeferencing. Inclusion of 3D volumetric structure of the current soft geo-objects simulation model would offer a substantial effort towards representing 3D soft geo-objects of SEOF dynamically within a basin by visualising saturated flow and overland flow volume. This research attempts to visualise the influence of a georeference system towards the dynamism of overland flow coverage and total overland flow volume generated from the SEOF process using VSG data structure. The data structure is driven by Green-Ampt methods and the Topographic Wetness Index (TWI). VSGs are analysed by focusing on spatial object preservation techniques of the conformal-based Malaysian Rectified Skew Orthomorphic (MRSO) and the equidistant-based Cassini-Soldner projection plane under the existing geodetic Malaysian Revised Triangulation 1948 (MRT48) and the newly implemented Geocentric Datum for Malaysia (GDM2000) datum. The simulated result visualises deformation of SEOF coverage under different georeference systems via its projection planes, which delineate dissimilar computation of SEOF areas and overland flow volumes. The integration of Georeference, 3D GIS and the saturation excess mechanism provides unifying evidence towards successful landslide and flood disaster management through envisioning the streamflow generating process (mainly SEOF) in a 3D environment.

  16. 3D phase micro-object studies by means of digital holographic tomography supported by algebraic reconstruction technique

    NASA Astrophysics Data System (ADS)

    Bilski, B. J.; Jozwicka, A.; Kujawinska, M.

    2007-09-01

    Constant development of microelements' technology requires a creation of new instruments to determine their basic physical parameters in 3D. The most efficient non-destructive method providing 3D information is tomography. In this paper we present Digital Holographic Tomography (DHT), in which input data is provided by means of Di-git- al Holography (DH). The main advantage of DH is the capability to capture several projections with a single hologram [1]. However, these projections have uneven angular distribution and their number is significantly limited. Therefore - Algebraic Reconstruction Technique (ART), where a few phase projections may be sufficient for proper 3D phase reconstruction, is implemented. The error analysis of the method and its additional limitations due to shape and dimensions of investigated object are presented. Finally, the results of ART application to DHT method are also presented on data reconstructed from numerically generated hologram of a multimode fibre.

  17. Visuo-haptic multisensory object recognition, categorization, and representation

    PubMed Central

    Lacey, Simon; Sathian, K.

    2014-01-01

    Visual and haptic unisensory object processing show many similarities in terms of categorization, recognition, and representation. In this review, we discuss how these similarities contribute to multisensory object processing. In particular, we show that similar unisensory visual and haptic representations lead to a shared multisensory representation underlying both cross-modal object recognition and view-independence. This shared representation suggests a common neural substrate and we review several candidate brain regions, previously thought to be specialized for aspects of visual processing, that are now known also to be involved in analogous haptic tasks. Finally, we lay out the evidence for a model of multisensory object recognition in which top-down and bottom-up pathways to the object-selective lateral occipital complex are modulated by object familiarity and individual differences in object and spatial imagery. PMID:25101014

  18. 3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events

    NASA Technical Reports Server (NTRS)

    Brown, Richard; Navard, Andrew; Spruce, Joseph

    2010-01-01

    An analytical, advanced imaging method has been developed for the initial monitoring and identification of foam debris and similar anomalies that occur post-launch in reference to the space shuttle s external tank (ET). Remote sensing technologies have been used to perform image enhancement and analysis on high-resolution, true-color images collected with the DCS 760 Kodak digital camera located in the right umbilical well of the space shuttle. Improvements to the camera, using filters, have added sharpness/definition to the image sets; however, image review/analysis of the ET has been limited by the fact that the images acquired by umbilical cameras during launch are two-dimensional, and are usually nonreferenceable between frames due to rotation translation of the ET as it falls away from the space shuttle. Use of stereo pairs of these images can enable strong visual indicators that can immediately portray depth perception of damaged areas or movement of fragments between frames is not perceivable in two-dimensional images. A stereoscopic image visualization system has been developed to allow 3D depth perception of stereo-aligned image pairs taken from in-flight umbilical and handheld digital shuttle cameras. This new system has been developed to augment and optimize existing 2D monitoring capabilities. Using this system, candidate sequential image pairs are identified for transformation into stereo viewing pairs. Image orientation is corrected using control points (similar points) between frames to place the two images in proper X-Y viewing perspective. The images are then imported into the WallView stereo viewing software package. The collected control points are used to generate a transformation equation that is used to re-project one image and effectively co-register it to the other image. The co-registered, oriented image pairs are imported into a WallView image set and are used as a 3D stereo analysis slide show. Multiple sequential image pairs can be used

  19. 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.

  20. 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). PMID:24554231

  1. A stroboscopic structured illumination system used in dynamic 3D visualization of high-speed motion object

    NASA Astrophysics Data System (ADS)

    Su, Xianyu; Zhang, Qican; Li, Yong; Xiang, Liqun; Cao, Yiping; Chen, Wenjing

    2005-04-01

    A stroboscopic structured illumination system, which can be used in measurement for 3D shape and deformation of high-speed motion object, is proposed and verified by experiments. The system, present in this paper, can automatically detect the position of high-speed moving object and synchronously control the flash of LED to project a structured optical field onto surface of motion object and the shoot of imaging system to acquire an image of deformed fringe pattern, also can create a signal, set artificially through software, to synchronously control the LED and imaging system to do their job. We experiment on a civil electric fan, successful acquire a serial of instantaneous, sharp and clear images of rotation blade and reconstruct its 3D shapes in difference revolutions.

  2. Object Recognition and Random Image Structure Evolution

    ERIC Educational Resources Information Center

    Sadr, Jvid; Sinha, Pawan

    2004-01-01

    We present a technique called Random Image Structure Evolution (RISE) for use in experimental investigations of high-level visual perception. Potential applications of RISE include the quantitative measurement of perceptual hysteresis and priming, the study of the neural substrates of object perception, and the assessment and detection of subtle…

  3. VIRO 3D: fast three-dimensional full-body scanning for humans and other living objects

    NASA Astrophysics Data System (ADS)

    Stein, Norbert; Minge, Bernhard

    1998-03-01

    The development of a family of partial and whole body scanners provides a complete technology for fully three-dimensional and contact-free scans on human bodies or other living objects within seconds. This paper gives insight into the design and the functional principles of the whole body scanner VIRO 3D operating on the basis of the laser split-beam method. The arrangement of up to 24 camera/laser combinations, thus dividing the area into different camera fields and an all- around sensor configuration travelling in vertical direction allow the complete 360-degree-scan of an object within 6 - 20 seconds. Due to a special calibration process the different sensors are matched and the measured data are combined. Up to 10 million 3D measuring points with a resolution of approximately 1 mm are processed in all coordinate axes to generate a 3D model. By means of high-performance processors in combination with real-time image processing chips the image data from almost any number of sensors can be recorded and evaluated synchronously in video real-time. VIRO 3D scanning systems have already been successfully implemented in various applications and will open up new perspectives in different other fields, ranging from industry, orthopaedic medicine, plastic surgery to art and photography.

  4. 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

  5. Controlled Experimental Study Depicting Moving Objects in View-Shared Time-Resolved 3D MRA

    PubMed Central

    Mostardi, Petrice M.; Haider, Clifton R.; Rossman, Phillip J.; Borisch, Eric A.; Riederer, Stephen J.

    2010-01-01

    Various methods have been used for time-resolved contrast-enhanced MRA (CE-MRA), many involving view sharing. However, the extent to which the resultant image time series represents the actual dynamic behavior of the contrast bolus is not always clear. Although numerical simulations can be used to estimate performance, an experimental study can allow more realistic characterization. The purpose of this work was to use a computer-controlled motion phantom for study of the temporal fidelity of 3D time-resolved sequences in depicting a contrast bolus. It is hypothesized that the view order of the acquisition and the selection of views in the reconstruction can affect the positional accuracy and sharpness of the leading edge of the bolus and artifactual signal preceding the edge. Phantom studies were performed using dilute gadolinium-filled vials that were moved along tabletop tracks by a computer-controlled motor. Several view orders were tested, which use view-sharing and Cartesian sampling. Compactness of measuring the k-space center, consistency of view ordering within each reconstruction frame, and sampling the k-space center near the end of the temporal footprint were shown to be important in accurate portrayal of the leading edge of the bolus. A number of findings were confirmed in an in vivo CE-MRA study. PMID:19319897

  6. Controlled experimental study depicting moving objects in view-shared time-resolved 3D MRA.

    PubMed

    Mostardi, Petrice M; Haider, Clifton R; Rossman, Phillip J; Borisch, Eric A; Riederer, Stephen J

    2009-07-01

    Various methods have been used for time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA), many involving view sharing. However, the extent to which the resultant image time series represents the actual dynamic behavior of the contrast bolus is not always clear. Although numerical simulations can be used to estimate performance, an experimental study can allow more realistic characterization. The purpose of this work was to use a computer-controlled motion phantom for study of the temporal fidelity of three-dimensional (3D) time-resolved sequences in depicting a contrast bolus. It is hypothesized that the view order of the acquisition and the selection of views in the reconstruction can affect the positional accuracy and sharpness of the leading edge of the bolus and artifactual signal preceding the edge. Phantom studies were performed using dilute gadolinium-filled vials that were moved along tabletop tracks by a computer-controlled motor. Several view orders were tested using view-sharing and Cartesian sampling. Compactness of measuring the k-space center, consistency of view ordering within each reconstruction frame, and sampling the k-space center near the end of the temporal footprint were shown to be important in accurate portrayal of the leading edge of the bolus. A number of findings were confirmed in an in vivo CE-MRA study. PMID:19319897

  7. 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.

  8. The effects of surface gloss and roughness on color constancy for real 3-D objects.

    PubMed

    Granzier, Jeroen J M; Vergne, Romain; Gegenfurtner, Karl R

    2014-01-01

    Color constancy denotes the phenomenon that the appearance of an object remains fairly stable under changes in illumination and background color. Most of what we know about color constancy comes from experiments using flat, matte surfaces placed on a single plane under diffuse illumination simulated on a computer monitor. Here we investigate whether material properties (glossiness and roughness) have an effect on color constancy for real objects. Subjects matched the color and brightness of cylinders (painted red, green, or blue) illuminated by simulated daylight (D65) or by a reddish light with a Munsell color book illuminated by a tungsten lamp. The cylinders were either glossy or matte and either smooth or rough. The object was placed in front of a black background or a colored checkerboard. We found that color constancy was significantly higher for the glossy objects compared to the matte objects, and higher for the smooth objects compared to the rough objects. This was independent of the background. We conclude that material properties like glossiness and roughness can have significant effects on color constancy. PMID:24563527

  9. Modeling 3-D objects with planar surfaces for prediction of electromagnetic scattering

    NASA Technical Reports Server (NTRS)

    Koch, M. B.; Beck, F. B.; Cockrell, C. R.

    1992-01-01

    Electromagnetic scattering analysis of objects at resonance is difficult because low frequency techniques are slow and computer intensive, and high frequency techniques may not be reliable. A new technique for predicting the electromagnetic backscatter from electrically conducting objects at resonance is studied. This technique is based on modeling three dimensional objects as a combination of flat plates where some of the plates are blocking the scattering from others. A cube is analyzed as a simple example. The preliminary results compare well with the Geometrical Theory of Diffraction and with measured data.

  10. Robust 3D object localization and pose estimation for random bin picking with the 3DMaMa algorithm

    NASA Astrophysics Data System (ADS)

    Skotheim, Øystein; Thielemann, Jens T.; Berge, Asbjørn; Sommerfelt, Arne

    2010-02-01

    Enabling robots to automatically locate and pick up randomly placed and oriented objects from a bin is an important challenge in factory automation, replacing tedious and heavy manual labor. A system should be able to recognize and locate objects with a predefined shape and estimate the position with the precision necessary for a gripping robot to pick it up. We describe a system that consists of a structured light instrument for capturing 3D data and a robust approach for object location and pose estimation. The method does not depend on segmentation of range images, but instead searches through pairs of 2D manifolds to localize candidates for object match. This leads to an algorithm that is not very sensitive to scene complexity or the number of objects in the scene. Furthermore, the strategy for candidate search is easily reconfigurable to arbitrary objects. Experiments reported in this paper show the utility of the method on a general random bin picking problem, in this paper exemplified by localization of car parts with random position and orientation. Full pose estimation is done in less than 380 ms per image. We believe that the method is applicable for a wide range of industrial automation problems where precise localization of 3D objects in a scene is needed.

  11. Line-Based Object Recognition using Hausdorff Distance: From Range Images to Molecular Secondary Structure

    SciTech Connect

    Guerra, C; Pascucci, V

    2004-12-13

    Object recognition algorithms are fundamental tools in automatic matching of geometric shapes within a background scene. Many approaches have been proposed in the past to solve the object recognition problem. Two of the key aspects that distinguish them in terms of their practical usability are: (i) the type of input model description and (ii) the comparison criteria used. In this paper we introduce a novel scheme for 3D object recognition based on line segment representation of the input shapes and comparison using the Hausdor distance. This choice of model representation provides the flexibility to apply the scheme in different application areas. We define several variants of the Hausdor distance to compare the models within the framework of well defined metric spaces. We present a matching algorithm that efficiently finds a pattern in a 3D scene. The algorithm approximates a minimization procedure of the Hausdor distance. The output error due to the approximation is guaranteed to be within a known constant bound. Practical results are presented for two classes of objects: (i) polyhedral shapes extracted from segmented range images and (ii) secondary structures of large molecules. In both cases the use of our approximate algorithm allows to match correctly the pattern in the background while achieving the efficiency necessary for practical use of the scheme. In particular the performance is improved substantially with minor degradation of the quality of the matching.

  12. An investigation of matching symmetry in the human pinnae with possible implications for 3D ear recognition and sound localization.

    PubMed

    Claes, Peter; Reijniers, Jonas; Shriver, Mark D; Snyders, Jonatan; Suetens, Paul; Nielandt, Joachim; De Tré, Guy; Vandermeulen, Dirk

    2015-01-01

    The human external ears, or pinnae, have an intriguing shape and, like most parts of the human external body, bilateral symmetry is observed between left and right. It is a well-known part of our auditory sensory system and mediates the spatial localization of incoming sounds in 3D from monaural cues due to its shape-specific filtering as well as binaural cues due to the paired bilateral locations of the left and right ears. Another less broadly appreciated aspect of the human pinna shape is its uniqueness from one individual to another, which is on the level of what is seen in fingerprints and facial features. This makes pinnae very useful in human identification, which is of great interest in biometrics and forensics. Anatomically, the type of symmetry observed is known as matching symmetry, with structures present as separate mirror copies on both sides of the body, and in this work we report the first such investigation of the human pinna in 3D. Within the framework of geometric morphometrics, we started by partitioning ear shape, represented in a spatially dense way, into patterns of symmetry and asymmetry, following a two-factor anova design. Matching symmetry was measured in all substructures of the pinna anatomy. However, substructures that 'stick out' such as the helix, tragus, and lobule also contained a fair degree of asymmetry. In contrast, substructures such as the conchae, antitragus, and antihelix expressed relatively stronger degrees of symmetric variation in relation to their levels of asymmetry. Insights gained from this study were injected into an accompanying identification setup exploiting matching symmetry where improved performance is demonstrated. Finally, possible implications of the results in the context of ear recognition as well as sound localization are discussed. PMID:25382291

  13. A 3D-1D substitution matrix for protein fold recognition that includes predicted secondary structure of the sequence.

    PubMed

    Rice, D W; Eisenberg, D

    1997-04-11

    In protein fold recognition, a probe amino acid sequence is compared to a library of representative folds of known structure to identify a structural homolog. In cases where the probe and its homolog have clear sequence similarity, traditional residue substitution matrices have been used to predict the structural similarity. In cases where the probe is sequentially distant from its homolog, we have developed a (7 x 3 x 2 x 7 x 3) 3D-1D substitution matrix (called H3P2), calculated from a database of 119 structural pairs. Members of each pair share a similar fold, but have sequence identity less than 30%. Each probe sequence position is defined by one of seven residue classes and three secondary structure classes. Each homologous fold position is defined by one of seven residue classes, three secondary structure classes, and two burial classes. Thus the matrix is five-dimensional and contains 7 x 3 x 2 x 7 x 3 = 882 elements or 3D-1D scores. The first step in assigning a probe sequence to its homologous fold is the prediction of the three-state (helix, strand, coil) secondary structure of the probe; here we use the profile based neural network prediction of secondary structure (PHD) program. Then a dynamic programming algorithm uses the H3P2 matrix to align the probe sequence with structures in a representative fold library. To test the effectiveness of the H3P2 matrix a challenging, fold class diverse, and cross-validated benchmark assessment is used to compare the H3P2 matrix to the GONNET, PAM250, BLOSUM62 and a secondary structure only substitution matrix. For distantly related sequences the H3P2 matrix detects more homologous structures at higher reliabilities than do these other substitution matrices, based on sensitivity versus specificity plots (or SENS-SPEC plots). The added efficacy of the H3P2 matrix arises from its information on the statistical preferences for various sequence-structure environment combinations from very distantly related proteins. It

  14. Microwave and camera sensor fusion for the shape extraction of metallic 3D space objects

    NASA Technical Reports Server (NTRS)

    Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

    1989-01-01

    The vacuum of space presents special problems for optical image sensors. Metallic objects in this environment can produce intense specular reflections and deep shadows. By combining the polarized RCS with an incomplete camera image, it has become possible to better determine the shape of some simple three-dimensional objects. The radar data are used in an iterative procedure that generates successive approximations to the target shape by minimizing the error between computed scattering cross-sections and the observed radar returns. Favorable results have been obtained for simulations and experiments reconstructing plates, ellipsoids, and arbitrary surfaces.

  15. Testing conditions for viewpoint invariance in object recognition.

    PubMed

    Hayward, W G; Tarr, M J

    1997-10-01

    Based on the geon structural description approach, I. Biederman and P.C. Gerhardstein (1993) proposed 3 conditions under which object recognition is predicted to be viewpoint invariant. Two experiments are reported that satisfied all 3 criteria yet revealed performance that was clearly viewpoint dependent. Experiment 1 demonstrated that for both sequential matching and naming tasks, recognition of qualitatively distinct objects became progressively longer and less accurate as the viewpoint difference between study and test viewpoints increased. Experiment 2 demonstrated that for single-part objects, larger effects of viewpoint occurred when there was a change in the visible structure, indicating sensitivity to qualitative features in the image, not geon structural descriptions. These results suggest that the conditions proposed by I. Biederman and P.C. Gerhardstein are not generally applicable, the recognition of qualitatively distinct objects often relies on viewpoint-dependent mechanisms, and the molar features of view-based mechanisms appear to be image features rather than geons. PMID:9411023

  16. Data amalgamation in the digitalization of 3D objects all over its 360 degrees

    NASA Astrophysics Data System (ADS)

    Rayas, Juan A.; Rodriguez-Vera, Ramon; Martinez, Amalia

    2005-02-01

    It is described a technique where different views of an object are connected to recover its three-dimensional form in a field of vision of 360°. The object is placed on a rotary motorized platform and projected a linear fringe pattern. In each angular object displacement, the projected fringe pattern is captured by a camera CCD. Each pattern is digitally demodulated providing information of depth. The format of the digital matrix, this is, the image type, is changed for one of triads (x, y, z). This way, a cloud of independent points of their position in the matrix is constructed. As a reference, one point in each cloud (known it a priori), is taken. All the clouds are rotated and displaced until the reference point taking its corresponding position. Different mixed clouds of points (views) are ordered in a single triad matrix that describes the complete surface of the object surface target. Finally a mesh of quadrilaterals is built up that makes possible to generate a solid surface.

  17. 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…

  18. Spontaneous Object Recognition Memory in Aged Rats: Complexity versus Similarity

    ERIC Educational Resources Information Center

    Gamiz, Fernando; Gallo, Milagros

    2012-01-01

    Previous work on the effect of aging on spontaneous object recognition (SOR) memory tasks in rats has yielded controversial results. Although the results at long-retention intervals are consistent, conflicting results have been reported at shorter delays. We have assessed the potential relevance of the type of object used in the performance of…

  19. Fusion of Depth and Intensity Data for Three-Dimensional Object Representation and Recognition

    NASA Astrophysics Data System (ADS)

    Ramirez Cortes, Juan Manuel

    For humans, retinal images provide sufficient information for the complete understanding of three-dimensional shapes in a scene. The ultimate goal of computer vision is to develop an automated system able to reproduce some of the tasks performed in a natural way by human beings as recognition, classification, or analysis of the environment as basis for further decisions. At the first level, referred to as early computer vision, the task is to extract symbolic descriptive information in a scene from a variety of sensory data. The second level is concerned with classification, recognition, or decision systems and the related heuristics, that aid the processing of the available information. This research is concerned with a new approach to 3-D object representation and recognition using an interpolation scheme applied to the information from the fusion of range and intensity data. The range image acquisition uses a methodology based on a passive stereo-vision model originally developed to be used with a sequence of images. However, curved features, large disparities and noisy input images are some of the problems associated with real imagery, which need to be addressed prior to applying the matching techniques in the spatial frequency domain. Some of the above mentioned problems can only be solved by computationally intensive spatial domain algorithms. Regularization techniques are explored for surface recovery from sparse range data, and intensity images are incorporated in the final representation of the surface. As an important application, the problem of 3-D representation of retinal images for extraction of quantitative information is addressed. Range information is also combined with intensity data to provide a more accurate numerical description based on aspect graphs. This representation is used as input to a three-dimensional object recognition system. Such an approach results in an improved performance of 3-D object classifiers.

  20. Dealing with uncertain feature assessments in interactive object recognition

    NASA Astrophysics Data System (ADS)

    Bauer, Alexander; Jürgens, Verena; Angele, Susanne

    2010-10-01

    Object recognition is a typical task of aerial reconnaissance and especially in military applications, to determine the class of an unknown object on the battlefield can give valuable information on its capabilities and its threat. RecceMan® (Reconnaissance Manual) is a decision support system for object recognition developed by the Fraunhofer IOSB. It supports object recognition by automating the tedious task of matching the object features with the set of possible object classes, while leaving the assessment of features to the trained human interpreter. The quality of the features assessed by the user is influenced by several factors such as the quality of the image of the object. These factors are potential sources of error, which can lead to an incorrect classification and therefore have to be considered by the system. To address this issue, two methods for consideration of uncertainty in human feature assessment - a probabilistic and a heuristic approach - are presented and compared based on an experiment in the exemplary domain of flower recognition.

  1. Calibration and 3D reconstruction of underwater objects with non-single-view projection model by structured light stereo imaging.

    PubMed

    Wang, Yexin; Negahdaripour, Shahriar; Aykin, Murat D

    2016-08-20

    Establishing the projection model of imaging systems is critical in 3D reconstruction of object shapes from multiple 2D views. When deployed underwater, these are enclosed in waterproof housings with transparent glass ports that generate nonlinear refractions of optical rays at interfaces, leading to invalidation of the commonly assumed single-viewpoint (SVP) model. In this paper, we propose a non-SVP ray tracing model for the calibration of a projector-camera system, employed for 3D reconstruction based on the structured light paradigm. The projector utilizes dot patterns, having established that the contrast loss is less severe than for traditional stripe patterns in highly turbid waters. Experimental results are presented to assess the achieved calibrating accuracy. PMID:27556973

  2. In-hand dexterous manipulation of piecewise-smooth 3-D objects

    SciTech Connect

    Rus, D.

    1999-04-01

    The author presents an algorithm called finger tracking for in-hand manipulation of three-dimensional objects with independent robot fingers. She describes and analyzes the differential control for finger tracking and extends it to on-line continuous control for a set of cooperating robot fingers. She shows experimental data from a simulation. Finally, she discusses global control issues for finger tracking, and computes lower bounds for reorientation by finger tracking. The algorithm is computationally efficient, exact, and takes into consideration the full dynamics of the system.

  3. 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.; pre="and">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.

  4. Object Recognition Method of Space Debris Tracking Image Sequence

    NASA Astrophysics Data System (ADS)

    Zhang, C.; Ping, Y. D.

    2015-09-01

    In order to strengthen the capability of the space debris researches, automated optical observation becomes more and more popular. Thus, the fully unattended automated object recognition framework is urgently needed to be studied. On the other hand, the open loop tracking which guides the telescope only with historical orbital elements is a simple and robust way to track space debris. According to the analysis of point distribution characteristics in pixel domain of object's open loop tracking image sequence, the Cluster Identification Method is introduced into automated space debris recognition method. With the comparison of three algorithm implements, it is shown that this method is totally available in actual research work.

  5. 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.

  6. A supervised method for object-based 3D building change detection on aerial stereo images

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  7. Calculations of Arctic ozone chemistry using objectively analyzed data in a 3-D CTM

    NASA Technical Reports Server (NTRS)

    Kaminski, J. W.; Mcconnell, J. C.; Sandilands, J. W.

    1994-01-01

    A three-dimensional chemical transport model (CTM) (Kaminski, 1992) has been used to study the evolution of the Arctic ozone during the winter of 1992. The continuity equation has been solved using a spectral method with Rhomboidal 15 (R15) truncation and leap-frog time stepping. Six-hourly meteorological fields from the Canadian Meteorological Center global objective analysis routines run at T79 were degraded to the model resolution. In addition, they were interpolated to the model time grid and were used to drive the model from the surface to 10 mb. In the model, processing of Cl(x) occurred over Arctic latitudes but some of the initial products were still present by mid-January. Also, the large amounts of ClO formed in the model in early January were converted to ClNO3. The results suggest that the model resolution may be insufficient to resolve the details of the Arctic transport during this time period. In particular, the wind field does not move the ClO(x) 'cloud' to the south over Europe as seen in the MLS measurements.

  8. Visual Exploration and Object Recognition by Lattice Deformation

    PubMed Central

    Melloni, Lucia; Mureşan, Raul C.

    2011-01-01

    Mechanisms of explicit object recognition are often difficult to investigate and require stimuli with controlled features whose expression can be manipulated in a precise quantitative fashion. Here, we developed a novel method (called “Dots”), for generating visual stimuli, which is based on the progressive deformation of a regular lattice of dots, driven by local contour information from images of objects. By applying progressively larger deformation to the lattice, the latter conveys progressively more information about the target object. Stimuli generated with the presented method enable a precise control of object-related information content while preserving low-level image statistics, globally, and affecting them only little, locally. We show that such stimuli are useful for investigating object recognition under a naturalistic setting – free visual exploration – enabling a clear dissociation between object detection and explicit recognition. Using the introduced stimuli, we show that top-down modulation induced by previous exposure to target objects can greatly influence perceptual decisions, lowering perceptual thresholds not only for object recognition but also for object detection (visual hysteresis). Visual hysteresis is target-specific, its expression and magnitude depending on the identity of individual objects. Relying on the particular features of dot stimuli and on eye-tracking measurements, we further demonstrate that top-down processes guide visual exploration, controlling how visual information is integrated by successive fixations. Prior knowledge about objects can guide saccades/fixations to sample locations that are supposed to be highly informative, even when the actual information is missing from those locations in the stimulus. The duration of individual fixations is modulated by the novelty and difficulty of the stimulus, likely reflecting cognitive demand. PMID:21818397

  9. A Hierarchical Control Strategy For 2-D Object Recognition

    NASA Astrophysics Data System (ADS)

    Cullen, Mark F.; Kuszmaul, Christopher L.; Ramsey, Timothy S.

    1988-02-01

    A control strategy for 2-D object recognition has been implemented on a hardware configuration which includes a Symbolics Lisp Machine (TM) as a front-end processor to a 16,384 processor Connection Machine (TM). The goal of this ongoing research program is to develop an image analysis system as an aid to human image interpretation experts. Our efforts have concentrated on 2-D object recognition in aerial imagery specifically, the detection and identification of aircraft near the Danbury, CT airport. Image processing functions to label and extract image features are implemented on the Connection Machine for robust computation. A model matching function was also designed and implemented on the CM for object recognition. In this paper we report on the integration of these algorithms on the CM, with a hierarchical control strategy to focus and guide the object recognition task to particular objects and regions of interest in imagery. It will be shown that these tech-nigues may be used to manipulate imagery on the order of 2k x 2k pixels in near-real-time.

  10. Individual differences in involvement of the visual object recognition system during visual word recognition.

    PubMed

    Laszlo, Sarah; Sacchi, Elizabeth

    2015-01-01

    Individuals with dyslexia often evince reduced activation during reading in left hemisphere (LH) language regions. This can be observed along with increased activation in the right hemisphere (RH), especially in areas associated with object recognition - a pattern referred to as RH compensation. The mechanisms of RH compensation are relatively unclear. We hypothesize that RH compensation occurs when the RH object recognition system is called upon to supplement an underperforming LH visual word form recognition system. We tested this by collecting ERPs while participants with a range of reading abilities viewed words, objects, and word/object ambiguous items (e.g., "SMILE" shaped like a smile). Less experienced readers differentiate words, objects, and ambiguous items less strongly, especially over the RH. We suggest that this lack of differentiation may have negative consequences for dyslexic individuals demonstrating RH compensation. PMID:25957504

  11. Reference Frames and 3-D Shape Perception of Pictured Objects: On Verticality and Viewpoint-From-Above

    PubMed Central

    van Doorn, Andrea J.; Wagemans, Johan

    2016-01-01

    Research on the influence of reference frames has generally focused on visual phenomena such as the oblique effect, the subjective visual vertical, the perceptual upright, and ambiguous figures. Another line of research concerns mental rotation studies in which participants had to discriminate between familiar or previously seen 2-D figures or pictures of 3-D objects and their rotated versions. In the present study, we disentangled the influence of the environmental and the viewer-centered reference frame, as classically done, by comparing the performances obtained in various picture and participant orientations. However, this time, the performance is the pictorial relief: the probed 3-D shape percept of the depicted object reconstructed from the local attitude settings of the participant. Comparisons between the pictorial reliefs based on different picture and participant orientations led to two major findings. First, in general, the pictorial reliefs were highly similar if the orientation of the depicted object was vertical with regard to the environmental or the viewer-centered reference frame. Second, a viewpoint-from-above interpretation could almost completely account for the shears occurring between the pictorial reliefs. More specifically, the shears could largely be considered as combinations of slants generated from the viewpoint-from-above, which was determined by the environmental as well as by the viewer-centered reference frame. PMID:27433329

  12. Spun-wrapped aligned nanofiber (SWAN) lithography for fabrication of micro/nano-structures on 3D objects.

    PubMed

    Ye, Zhou; Nain, Amrinder S; Behkam, Bahareh

    2016-07-01

    Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for fabrication of multiscale (nano to microscale) structures on 3D objects without restriction on substrate material and geometry. SWAN lithography combines precise deposition of polymeric nanofiber masks, in aligned single or multilayer configurations, with well-controlled solvent vapor treatment and etching processes to enable high throughput (>10(-7) m(2) s(-1)) and large-area fabrication of sub-50 nm to several micron features with high pattern fidelity. Using this technique, we demonstrate whole-surface nanopatterning of bulk and thin film surfaces of cubes, cylinders, and hyperbola-shaped objects that would be difficult, if not impossible to achieve with existing methods. We demonstrate that the fabricated feature size (b) scales with the fiber mask diameter (D) as b(1.5)∝D. This scaling law is in excellent agreement with theoretical predictions using the Johnson, Kendall, and Roberts (JKR) contact theory, thus providing a rational design framework for fabrication of systems and devices that require precisely designed multiscale features. PMID:27283144

  13. An effective 3D leapfrog scheme for electromagnetic modelling of arbitrary shaped dielectric objects using unstructured meshes

    NASA Astrophysics Data System (ADS)

    Gansen, A.; El Hachemi, M.; Belouettar, S.; Hassan, O.; Morgan, K.

    2015-12-01

    In computational electromagnetics, the advantages of the standard Yee algorithm are its simplicity and its low computational costs. However, because of the accuracy losses resulting from the staircased representation of curved interfaces, it is normally not the method of choice for modelling electromagnetic interactions with objects of arbitrary shape. For these problems, an unstructured mesh finite volume time domain method is often employed, although the scheme does not satisfy the divergence free condition at the discrete level. In this paper, we generalize the standard Yee algorithm for use on unstructured meshes and solve the problem concerning the loss of accuracy linked to staircasing, while preserving the divergence free nature of the algorithm. The scheme is implemented on high quality primal Delaunay and dual Voronoi meshes. The performance of the approach was validated in previous work by simulating the scattering of electromagnetic waves by spherical 3D PEC objects in free space. In this paper we demonstrate the performance of this scheme for penetration problems in lossy dielectrics using a new averaging technique for Delaunay and Voronoi edges at the interface. A detailed explanation of the implementation of the method, and a demonstration of the quality of the results obtained for transmittance and scattering simulations by 3D objects of arbitrary shapes, are presented.

  14. Parallel phase-shifting digital holography and its application to high-speed 3D imaging of dynamic object

    NASA Astrophysics Data System (ADS)

    Awatsuji, Yasuhiro; Xia, Peng; Wang, Yexin; Matoba, Osamu

    2016-03-01

    Digital holography is a technique of 3D measurement of object. The technique uses an image sensor to record the interference fringe image containing the complex amplitude of object, and numerically reconstructs the complex amplitude by computer. Parallel phase-shifting digital holography is capable of accurate 3D measurement of dynamic object. This is because this technique can reconstruct the complex amplitude of object, on which the undesired images are not superimposed, form a single hologram. The undesired images are the non-diffraction wave and the conjugate image which are associated with holography. In parallel phase-shifting digital holography, a hologram, whose phase of the reference wave is spatially and periodically shifted every other pixel, is recorded to obtain complex amplitude of object by single-shot exposure. The recorded hologram is decomposed into multiple holograms required for phase-shifting digital holography. The complex amplitude of the object is free from the undesired images is reconstructed from the multiple holograms. To validate parallel phase-shifting digital holography, a high-speed parallel phase-shifting digital holography system was constructed. The system consists of a Mach-Zehnder interferometer, a continuous-wave laser, and a high-speed polarization imaging camera. Phase motion picture of dynamic air flow sprayed from a nozzle was recorded at 180,000 frames per second (FPS) have been recorded by the system. Also phase motion picture of dynamic air induced by discharge between two electrodes has been recorded at 1,000,000 FPS, when high voltage was applied between the electrodes.

  15. Towards Perceptual Interface for Visualization Navigation of Large Data Sets Using Gesture Recognition with Bezier Curves and Registered 3-D Data

    SciTech Connect

    Shin, M C; Tsap, L V; Goldgof, D B

    2003-03-20

    This paper presents a gesture recognition system for visualization navigation. Scientists are interested in developing interactive settings for exploring large data sets in an intuitive environment. The input consists of registered 3-D data. A geometric method using Bezier curves is used for the trajectory analysis and classification of gestures. The hand gesture speed is incorporated into the algorithm to enable correct recognition from trajectories with variations in hand speed. The method is robust and reliable: correct hand identification rate is 99.9% (from 1641 frames), modes of hand movements are correct 95.6% of the time, recognition rate (given the right mode) is 97.9%. An application to gesture-controlled visualization of 3D bioinformatics data is also presented.

  16. A novel multi-view object recognition in complex background

    NASA Astrophysics Data System (ADS)

    Chang, Yongxin; Yu, Huapeng; Xu, Zhiyong; Fu, Chengyu; Gao, Chunming

    2015-02-01

    Recognizing objects from arbitrary aspects is always a highly challenging problem in computer vision, and most existing algorithms mainly focus on a specific viewpoint research. Hence, in this paper we present a novel recognizing framework based on hierarchical representation, part-based method and learning in order to recognize objects from different viewpoints. The learning evaluates the model's mistakes and feeds it back the detector to avid the same mistakes in the future. The principal idea is to extract intrinsic viewpoint invariant features from the unseen poses of object, and then to take advantage of these shared appearance features to support recognition combining with the improved multiple view model. Compared with other recognition models, the proposed approach can efficiently tackle multi-view problem and promote the recognition versatility of our system. For an quantitative valuation The novel algorithm has been tested on several benchmark datasets such as Caltech 101 and PASCAL VOC 2010. The experimental results validate that our approach can recognize objects more precisely and the performance outperforms others single view recognition methods.

  17. What are the Visual Features Underlying Rapid Object Recognition?

    PubMed Central

    Crouzet, Sébastien M.; Serre, Thomas

    2011-01-01

    Research progress in machine vision has been very significant in recent years. Robust face detection and identification algorithms are already readily available to consumers, and modern computer vision algorithms for generic object recognition are now coping with the richness and complexity of natural visual scenes. Unlike early vision models of object recognition that emphasized the role of figure-ground segmentation and spatial information between parts, recent successful approaches are based on the computation of loose collections of image features without prior segmentation or any explicit encoding of spatial relations. While these models remain simplistic models of visual processing, they suggest that, in principle, bottom-up activation of a loose collection of image features could support the rapid recognition of natural object categories and provide an initial coarse visual representation before more complex visual routines and attentional mechanisms take place. Focusing on biologically plausible computational models of (bottom-up) pre-attentive visual recognition, we review some of the key visual features that have been described in the literature. We discuss the consistency of these feature-based representations with classical theories from visual psychology and test their ability to account for human performance on a rapid object categorization task. PMID:22110461

  18. 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

  19. Workflows and the Role of Images for Virtual 3d Reconstruction of no Longer Extant Historic Objects

    NASA Astrophysics Data System (ADS)

    Münster, S.

    2013-07-01

    3D reconstruction technologies have gained importance as tools for the research and visualization of no longer extant historic objects during the last decade. Within such reconstruction processes, visual media assumes several important roles: as the most important sources especially for a reconstruction of no longer extant objects, as a tool for communication and cooperation within the production process, as well as for a communication and visualization of results. While there are many discourses about theoretical issues of depiction as sources and as visualization outcomes of such projects, there is no systematic research about the importance of depiction during a 3D reconstruction process and based on empirical findings. Moreover, from a methodological perspective, it would be necessary to understand which role visual media plays during the production process and how it is affected by disciplinary boundaries and challenges specific to historic topics. Research includes an analysis of published work and case studies investigating reconstruction projects. This study uses methods taken from social sciences to gain a grounded view of how production processes would take place in practice and which functions and roles images would play within them. For the investigation of these topics, a content analysis of 452 conference proceedings and journal articles related to 3D reconstruction modeling in the field of humanities has been completed. Most of the projects described in those publications dealt with data acquisition and model building for existing objects. Only a small number of projects focused on structures that no longer or never existed physically. Especially that type of project seems to be interesting for a study of the importance of pictures as sources and as tools for interdisciplinary cooperation during the production process. In the course of the examination the authors of this paper applied a qualitative content analysis for a sample of 26 previously

  20. 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

  1. Evidence that the rat hippocampus has contrasting roles in object recognition memory and object recency memory.

    PubMed

    Albasser, Mathieu M; Amin, Eman; Lin, Tzu-Ching E; Iordanova, Mihaela D; Aggleton, John P

    2012-10-01

    Adult rats with extensive, bilateral neurotoxic lesions of the hippocampus showed normal forgetting curves for object recognition memory, yet were impaired on closely related tests of object recency memory. The present findings point to specific mechanisms for temporal order information (recency) that are dependent on the hippocampus and do not involve object recognition memory. The object recognition tests measured rats exploring simultaneously presented objects, one novel and the other familiar. Task difficulty was varied by altering the retention delays after presentation of the familiar object, so creating a forgetting curve. Hippocampal lesions had no apparent effect, despite using an apparatus (bow-tie maze) where it was possible to give lists of objects that might be expected to increase stimulus interference. In contrast, the same hippocampal lesions impaired the normal preference for an older (less recent) familiar object over a more recent, familiar object. A correlation was found between the loss of septal hippocampal tissue and this impairment in recency memory. The dissociation in the present study between recognition memory (spared) and recency memory (impaired) was unusually compelling, because it was possible to test the same objects for both forms of memory within the same session and within the same apparatus. The object recency deficit is of additional interest as it provides an example of a nonspatial memory deficit following hippocampal damage. PMID:23025831

  2. 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

  3. Priming for novel object associations: Neural differences from object item priming and equivalent forms of recognition.

    PubMed

    Gomes, Carlos Alexandre; Figueiredo, Patrícia; Mayes, Andrew

    2016-04-01

    The neural substrates of associative and item priming and recognition were investigated in a functional magnetic resonance imaging study over two separate sessions. In the priming session, participants decided which object of a pair was bigger during both study and test phases. In the recognition session, participants saw different object pairs and performed the same size-judgement task followed by an associative recognition memory task. Associative priming was accompanied by reduced activity in the right middle occipital gyrus as well as in bilateral hippocampus. Object item priming was accompanied by reduced activity in extensive priming-related areas in the bilateral occipitotemporofrontal cortex, as well as in the perirhinal cortex, but not in the hippocampus. Associative recognition was characterized by activity increases in regions linked to recollection, such as the hippocampus, posterior cingulate cortex, anterior medial frontal gyrus and posterior parahippocampal cortex. Item object priming and recognition recruited broadly overlapping regions (e.g., bilateral middle occipital and prefrontal cortices, left fusiform gyrus), even though the BOLD response was in opposite directions. These regions along with the precuneus, where both item priming and recognition were accompanied by activation, have been found to respond to object familiarity. The minimal structural overlap between object associative priming and recollection-based associative recognition suggests that they depend on largely different stimulus-related information and that the different directions of the effects indicate distinct retrieval mechanisms. In contrast, item priming and familiarity-based recognition seemed mainly based on common memory information, although the extent of common processing between priming and familiarity remains unclear. Further implications of these findings are discussed. © 2015 Wiley Periodicals, Inc. PMID:26418396

  4. Human cortical object recognition from a visual motion flowfield.

    PubMed

    Kriegeskorte, Nikolaus; Sorger, Bettina; Naumer, Marcus; Schwarzbach, Jens; van den Boogert, Erik; Hussy, Walter; Goebel, Rainer

    2003-02-15

    Moving dots can evoke a percept of the spatial structure of a three-dimensional object in the absence of other visual cues. This phenomenon, called structure from motion (SFM), suggests that the motion flowfield represented in the dorsal stream can form the basis of object recognition performed in the ventral stream. SFM processing is likely to contribute to object perception whenever there is relative motion between the observer and the object viewed. Here we investigate the motion flowfield component of object recognition with functional magnetic resonance imaging. Our SFM stimuli encoded face surfaces and random three-dimensional control shapes with matched curvature properties. We used two different types of an SFM stimulus with the dots either fixed to the surface of the object or moving on it. Despite the radically different encoding of surface structure in the two types of SFM, both elicited strong surface percepts and involved the same network of cortical regions. From early visual areas, this network extends dorsally into the human motion complex and parietal regions and ventrally into object-related cortex. The SFM stimuli elicited a face-selective response in the fusiform face area. The human motion complex appears to have a central role in SFM object recognition, not merely representing the motion flowfield but also the surface structure of the motion-defined object. The motion complex and a region in the intraparietal sulcus reflected the motion state of the SFM-implicit object, responding more strongly when the implicit object was in motion than when it was stationary. PMID:12598634

  5. Multi-frequency color-marked fringe projection profilometry for fast 3D shape measurement of complex objects.

    PubMed

    Jiang, Chao; Jia, Shuhai; Dong, Jun; Bao, Qingchen; Yang, Jia; Lian, Qin; Li, Dichen

    2015-09-21

    We propose a novel multi-frequency color-marked fringe projection profilometry approach to measure the 3D shape of objects with depth discontinuities. A digital micromirror device projector is used to project a color map consisting of a series of different-frequency color-marked fringe patterns onto the target object. We use a chromaticity curve to calculate the color change caused by the height of the object. The related algorithm to measure the height is also described in this paper. To improve the measurement accuracy, a chromaticity curve correction method is presented. This correction method greatly reduces the influence of color fluctuations and measurement error on the chromaticity curve and the calculation of the object height. The simulation and experimental results validate the utility of our method. Our method avoids the conventional phase shifting and unwrapping process, as well as the independent calculation of the object height required by existing techniques. Thus, it can be used to measure complex and dynamic objects with depth discontinuities. These advantages are particularly promising for industrial applications. PMID:26406621

  6. Colorful holographic display of 3D object based on scaled diffraction by using non-uniform fast Fourier transform

    NASA Astrophysics Data System (ADS)

    Chang, Chenliang; Xia, Jun; Lei, Wei

    2015-03-01

    We proposed a new method to calculate the color computer generated hologram of three-dimensional object in holographic display. The three-dimensional object is composed of several tilted planes which are tilted from the hologram. The diffraction from each tilted plane to the hologram plane is calculated based on the coordinate rotation in Fourier spectrum domains. We used the nonuniform fast Fourier transformation (NUFFT) to calculate the nonuniform sampled Fourier spectrum on the tilted plane after coordinate rotation. By using the NUFFT, the diffraction calculation from tilted plane to the hologram plane with variable sampling rates can be achieved, which overcomes the sampling restriction of FFT in the conventional angular spectrum based method. The holograms of red, green and blue component of the polygon-based object are calculated separately by using our NUFFT based method. Then the color hologram is synthesized by placing the red, green and blue component hologram in sequence. The chromatic aberration caused by the wavelength difference can be solved effectively by restricting the sampling rate of the object in the calculation of each wavelength component. The computer simulation shows the feasibility of our method in calculating the color hologram of polygon-based object. The 3D object can be displayed in color with adjustable size and no chromatic aberration in holographic display system, which can be considered as an important application in the colorful holographic three-dimensional display.

  7. Methods for recognition of natural and man-made objects using laser radar data

    NASA Astrophysics Data System (ADS)

    Groenwall, Christina A.; Chevalier, Tomas R.; Persson, Asa; Elmqvist, Magnus; Ahlberg, Simon; Klasen, Lena M.; Andersson, Pierre

    2004-09-01

    Over the years imaging laser radar systems have been developed for both military and civilian (topographic) applications. Among the applications, 3D data is used for environment modeling and object reconstruction and recognition. The data processing methods are mainly developed separately for military or topographic applications, seldom both application areas are in mind. In this paper, an overview of methods from both areas is presented. First, some of the work on ground surface estimation and classification of natural objects, for example trees, is described. Once natural objects have been detected and classified, we review some of the extensive work on reconstruction and recognition of man-made objects. Primarily we address the reconstruction of buildings and recognition of vehicles. Further, some methods for evaluation of measurement systems and algorithms are described. Models of some types of laser radar systems are reviewed, based on both physical and statistical approaches, for analysis and evaluation of measurement systems and algorithms. The combination of methods for reconstruction of natural and man-made objects is also discussed. By combining methods originating from civilian and military applications, we believe that the tools to analyze a whole scene become available. In this paper we show examples where methods from both application fields are used to analyze a scene.

  8. Qualitative and quantitative characterization of surface and volumetric properties of objects for recognition

    NASA Astrophysics Data System (ADS)

    Zlateva, Stoyanka D.

    1995-10-01

    Recently advanced computational theories of 3D shape representation for recognition have focused on the alternative of viewer-centered vs. object-centered representation. Both approaches rely on establishing a correspondence between image data and the prototypical knowledge of object shape. This paper discusses the mathematical structures needed for organizing prototypical knowledge of object shape in a way that naturally relies to perceptual categories and thus allows for a flexible and efficient recognition process. The representational schema consists of a configuration of boundary based constituent parts which build the reference frame for qualitative and quantitative shape attributes. The decomposition into constituent parts maximizes convexity regions of the bounding surface and relies on extending the local classification into elliptic, hyperbolic, plane and parabolic to globally convex and nonconvex surface regions. The surface type of the parts guides and is preserved in a subsequent part approximation through generalized cones as volumetric primitives. This approach allows for a consistent characterization of surface and volumetric properties of object shape. A secondary segmentation into sub-parts and associated features is defined by the surface type and the type of change in cross section area along the axis. The two segmentation levels allows for a detailed and elaborate shape description. We show examples of shape description and discuss the representation in relation to the viewer-centered and object centered approaches to recognition.

  9. 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.

  10. Feature based recognition of submerged objects in holographic imagery

    NASA Astrophysics Data System (ADS)

    Ratto, Christopher R.; Beagley, Nathaniel; Baldwin, Kevin C.; Shipley, Kara R.; Sternberger, Wayne I.

    2014-05-01

    The ability to autonomously sense and characterize underwater objects in situ is desirable in applications of unmanned underwater vehicles (UUVs). In this work, underwater object recognition was explored using a digital holographic system. Two experiments were performed in which several objects of varying size, shape, and material were submerged in a 43,000 gallon test tank. Holograms were collected from each object at multiple distances and orientations, with the imager located either outside the tank (looking through a porthole) or submerged (looking downward). The resultant imagery from these holograms was preprocessed to improve dynamic range, mitigate speckle, and segment out the image of the object. A collection of feature descriptors were then extracted from the imagery to characterize various object properties (e.g., shape, reflectivity, texture). The features extracted from images of multiple objects, collected at different imaging geometries, were then used to train statistical models for object recognition tasks. The resulting classification models were used to perform object classification as well as estimation of various parameters of the imaging geometry. This information can then be used to inform the design of autonomous sensing algorithms for UUVs employing holographic imagers.

  11. Spun-wrapped aligned nanofiber (SWAN) lithography for fabrication of micro/nano-structures on 3D objects

    NASA Astrophysics Data System (ADS)

    Ye, Zhou; Nain, Amrinder S.; Behkam, Bahareh

    2016-06-01

    Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for fabrication of multiscale (nano to microscale) structures on 3D objects without restriction on substrate material and geometry. SWAN lithography combines precise deposition of polymeric nanofiber masks, in aligned single or multilayer configurations, with well-controlled solvent vapor treatment and etching processes to enable high throughput (>10-7 m2 s-1) and large-area fabrication of sub-50 nm to several micron features with high pattern fidelity. Using this technique, we demonstrate whole-surface nanopatterning of bulk and thin film surfaces of cubes, cylinders, and hyperbola-shaped objects that would be difficult, if not impossible to achieve with existing methods. We demonstrate that the fabricated feature size (b) scales with the fiber mask diameter (D) as b1.5 ~ D. This scaling law is in excellent agreement with theoretical predictions using the Johnson, Kendall, and Roberts (JKR) contact theory, thus providing a rational design framework for fabrication of systems and devices that require precisely designed multiscale features.Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for

  12. Geometric filtration of classification-based object detectors in realtime road scene recognition systems

    NASA Astrophysics Data System (ADS)

    Prun, Viktor; Bocharov, Dmitry; Koptelov, Ivan; Sholomov, Dmitry; Postnikov, Vassily

    2015-12-01

    We study the issue of performance improvement of classification-based object detectors by including certain geometric-oriented filters. Configurations of the observed 3D scene may be used as a priori or a posteriori information for object filtration. A priori information is used to select only those object parameters (size and position on image plane) that are in accordance with the scene, restricting implausible combinations of parameters. On the other hand the detection robustness can be enhanced by rejecting detection results using a posteriori information about 3D scene. For example, relative location of detected objects can be used as criteria for filtration. We have included proposed filters in object detection modules of two different industrial vision-based recognition systems and compared the resulting detection quality before detectors improving and after. Filtering with a priori information leads to significant decrease of detector's running time per frame and increase of number of correctly detected objects. Including filter based on a posteriori information leads to decrease of object detection false positive rate.

  13. Top-down facilitation of visual object recognition: object-based and context-based contributions.

    PubMed

    Fenske, Mark J; Aminoff, Elissa; Gronau, Nurit; Bar, Moshe

    2006-01-01

    The neural mechanisms subserving visual recognition are traditionally described in terms of bottom-up analysis, whereby increasingly complex aspects of the visual input are processed along a hierarchical progression of cortical regions. However, the importance of top-down facilitation in successful recognition has been emphasized in recent models and research findings. Here we consider evidence for top-down facilitation of recognition that is triggered by early information about an object, as well as by contextual associations between an object and other objects with which it typically appears. The object-based mechanism is proposed to trigger top-down facilitation of visual recognition rapidly, using a partially analyzed version of the input image (i.e., a blurred image) that is projected from early visual areas directly to the prefrontal cortex (PFC). This coarse representation activates in the PFC information that is back-projected as "initial guesses" to the temporal cortex where it presensitizes the most likely interpretations of the input object. In addition to this object-based facilitation, a context-based mechanism is proposed to trigger top-down facilitation through contextual associations between objects in scenes. These contextual associations activate predictive information about which objects are likely to appear together, and can influence the "initial guesses" about an object's identity. We have shown that contextual associations are analyzed by a network that includes the parahippocampal cortex and the retrosplenial complex. The integrated proposal described here is that object- and context-based top-down influences operate together, promoting efficient recognition by framing early information about an object within the constraints provided by a lifetime of experience with contextual associations. PMID:17027376

  14. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    PubMed Central

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-01-01

    We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet. PMID:27375939

  15. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    DOE PAGESBeta

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-05-01

    Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single moleculemore » super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.« less

  16. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution.

    PubMed

    Meddens, Marjolein B M; Liu, Sheng; Finnegan, Patrick S; Edwards, Thayne L; James, Conrad D; Lidke, Keith A

    2016-06-01

    We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet. PMID:27375939

  17. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    SciTech Connect

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-01-01

    Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.

  18. Temporal scales of auditory objects underlying birdsong vocal recognition

    PubMed Central

    Gentner, Timothy Q.

    2008-01-01

    Vocal recognition is common among songbirds, and provides an excellent model system to study the perceptual and neurobiological mechanisms for processing natural vocal communication signals. Male European starlings, a species of songbird, learn to recognize the songs of multiple conspecific males by attending to stereotyped acoustic patterns, and these learned patterns elicit selective neuronal responses in auditory forebrain neurons. The present study investigates the perceptual grouping of spectrotemporal acoustic patterns in starling song at multiple temporal scales. The results show that permutations in sequencing of submotif acoustic features have significant effects on song recognition, and that these effects are specific to songs that comprise learned motifs. The observations suggest that (1) motifs form auditory objects embedded in a hierarchy of acoustic patterns, (2) that object-based song perception emerges without explicit reinforcement, and (3) that multiple temporal scales within the acoustic pattern hierarchy convey information about the individual identity of the singer. The authors discuss the results in the context of auditory object formation and talker recognition. PMID:18681620

  19. A hybrid learning approach for better recognition of visual objects

    SciTech Connect

    Imam, I.F.; Gutta, S.

    1996-12-31

    Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of these visual alterations. This paper presents a novel approach for learning optimized structures of classifiers for recognizing visual objects regardless of certain types of visual alterations. The approach consists of two phases. The first phase is concerned with learning classifications of a set of standard and altered objects. The second phase is concerned with discovering an optimized structure of classifiers for recognizing objects from unseen images. This paper presents an application of this approach to a domain of 15 classes of hand gestures. The experimental results show significant improvement in the recognition rate rather than using a single classifier or multiple classifiers with thresholds.

  20. Early recurrent feedback facilitates visual object recognition under challenging conditions

    PubMed Central

    Wyatte, Dean; Jilk, David J.; O'Reilly, Randall C.

    2014-01-01

    Standard models of the visual object recognition pathway hold that a largely feedforward process from the retina through inferotemporal cortex leads to object identification. A subsequent feedback process originating in frontoparietal areas through reciprocal connections to striate cortex provides attentional support to salient or behaviorally-relevant features. Here, we review mounting evidence that feedback signals also originate within extrastriate regions and begin during the initial feedforward process. This feedback process is temporally dissociable from attention and provides important functions such as grouping, associational reinforcement, and filling-in of features. Local feedback signals operating concurrently with feedforward processing are important for object identification in noisy real-world situations, particularly when objects are partially occluded, unclear, or otherwise ambiguous. Altogether, the dissociation of early and late feedback processes presented here expands on current models of object identification, and suggests a dual role for descending feedback projections. PMID:25071647

  1. See-Through Imaging of Laser-Scanned 3d Cultural Heritage Objects Based on Stochastic Rendering of Large-Scale Point Clouds

    NASA Astrophysics Data System (ADS)

    Tanaka, S.; Hasegawa, K.; Okamoto, N.; Umegaki, R.; Wang, S.; Uemura, M.; Okamoto, A.; Koyamada, K.

    2016-06-01

    We propose a method for the precise 3D see-through imaging, or transparent visualization, of the large-scale and complex point clouds acquired via the laser scanning of 3D cultural heritage objects. Our method is based on a stochastic algorithm and directly uses the 3D points, which are acquired using a laser scanner, as the rendering primitives. This method achieves the correct depth feel without requiring depth sorting of the rendering primitives along the line of sight. Eliminating this need allows us to avoid long computation times when creating natural and precise 3D see-through views of laser-scanned cultural heritage objects. The opacity of each laser-scanned object is also flexibly controllable. For a laser-scanned point cloud consisting of more than 107 or 108 3D points, the pre-processing requires only a few minutes, and the rendering can be executed at interactive frame rates. Our method enables the creation of cumulative 3D see-through images of time-series laser-scanned data. It also offers the possibility of fused visualization for observing a laser-scanned object behind a transparent high-quality photographic image placed in the 3D scene. We demonstrate the effectiveness of our method by applying it to festival floats of high cultural value. These festival floats have complex outer and inner 3D structures and are suitable for see-through imaging.

  2. 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

  3. 3D SMoSIFT: three-dimensional sparse motion scale invariant feature transform for activity recognition from RGB-D videos

    NASA Astrophysics Data System (ADS)

    Wan, Jun; Ruan, Qiuqi; Li, Wei; An, Gaoyun; Zhao, Ruizhen

    2014-03-01

    Human activity recognition based on RGB-D data has received more attention in recent years. We propose a spatiotemporal feature named three-dimensional (3D) sparse motion scale-invariant feature transform (SIFT) from RGB-D data for activity recognition. First, we build pyramids as scale space for each RGB and depth frame, and then use Shi-Tomasi corner detector and sparse optical flow to quickly detect and track robust keypoints around the motion pattern in the scale space. Subsequently, local patches around keypoints, which are extracted from RGB-D data, are used to build 3D gradient and motion spaces. Then SIFT-like descriptors are calculated on both 3D spaces, respectively. The proposed feature is invariant to scale, transition, and partial occlusions. More importantly, the running time of the proposed feature is fast so that it is well-suited for real-time applications. We have evaluated the proposed feature under a bag of words model on three public RGB-D datasets: one-shot learning Chalearn Gesture Dataset, Cornell Activity Dataset-60, and MSR Daily Activity 3D dataset. Experimental results show that the proposed feature outperforms other spatiotemporal features and are comparative to other state-of-the-art approaches, even though there is only one training sample for each class.

  4. Object recognition by component features: are there age differences.

    PubMed

    Frazier, L; Hoyer, W J

    1992-01-01

    This study extended aspects of Biederman's (1987) recognition-by-components (RBC) theory to the analysis of age differences in the recognition of incomplete visually-presented objects. RBC theory predicts that objects are recognizable or recoverable under conditions of fragmentation if a sufficient amount of essential structural information remains available. Objects are rendered nonrecoverable by the omission or obstruction of essential structural features at vertices and areas of concavity. Fifteen young adults and 15 older adults participated in a study of the effects of amount (25%, 45%, 65%) and type of fragmentation (recoverable, nonrecoverable) on object naming. Age-related declines in recognizing incomplete objects were associated with the amount of fragmentation, but type of fragmentation did not affect the performance of older adults. For the young adults, accuracy of performance was affected by both amount and type of fragmentation, consistent with Biederman's RBC theory. These results were interpreted as suggesting that age-related declines in perceptual closure performance have to do with non-structural factors such as the ability to inferentially augment degraded or missing visual information. PMID:1446700

  5. The role of spatial frequency in expert object recognition.

    PubMed

    Hagen, Simen; Vuong, Quoc C; Scott, Lisa S; Curran, Tim; Tanaka, James W

    2016-03-01

    Novices recognize objects at the basic-category level (e.g., dog, chair, and bird) at which identification is based on the global form of the objects (Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976). In contrast, experts recognize objects within their domain of expertise at the subordinate level (e.g., Sparrow or Finch) for which the internal object information may play an important role in identification (Tanaka & Taylor, 1991). To investigate whether expert recognition relies on internal object information, we band-pass filtered bird images over a range of spatial frequencies (SF) and then masked the filtered image to preserve its global form. In Experiment 1, bird experts categorized common birds at the family level (e.g., Robin or Sparrow) more quickly and more accurately than novices. Both experts and novices were more accurate when bird images contained the internal information represented by a middle range of SFs, and this finding was characterized by a quadratic function in which accuracy decreased toward each end of the SF spectrum. However, the experts, but not the novices, showed a similar quadratic relationship between response times and SF range. In Experiment 2, experts categorized Warblers and Finches at the more specific, species level (e.g., Wilson's Warbler or House Finch). Recognition was again fastest and most accurate for images filtered in the middle range of SFs. Collectively, these results indicate that a midrange of SFs contain crucial information for subordinate recognition, and that extensive perceptual experience can influence the efficiency with which this information is utilized. (PsycINFO Database Record PMID:26480250

  6. Visual appearance interacts with conceptual knowledge in object recognition.

    PubMed

    Cheung, Olivia S; Gauthier, Isabel

    2014-01-01

    Objects contain rich visual and conceptual information, but do these two types of information interact? Here, we examine whether visual and conceptual information interact when observers see novel objects for the first time. We then address how this interaction influences the acquisition of perceptual expertise. We used two types of novel objects (Greebles), designed to resemble either animals or tools, and two lists of words, which described non-visual attributes of people or man-made objects. Participants first judged if a word was more suitable for describing people or objects while ignoring a task-irrelevant image, and showed faster responses if the words and the unfamiliar objects were congruent in terms of animacy (e.g., animal-like objects with words that described human). Participants then learned to associate objects and words that were either congruent or not in animacy, before receiving expertise training to rapidly individuate the objects. Congruent pairing of visual and conceptual information facilitated observers' ability to become a perceptual expert, as revealed in a matching task that required visual identification at the basic or subordinate levels. Taken together, these findings show that visual and conceptual information interact at multiple levels in object recognition. PMID:25120509

  7. Visual appearance interacts with conceptual knowledge in object recognition

    PubMed Central

    Cheung, Olivia S.; Gauthier, Isabel

    2014-01-01

    Objects contain rich visual and conceptual information, but do these two types of information interact? Here, we examine whether visual and conceptual information interact when observers see novel objects for the first time. We then address how this interaction influences the acquisition of perceptual expertise. We used two types of novel objects (Greebles), designed to resemble either animals or tools, and two lists of words, which described non-visual attributes of people or man-made objects. Participants first judged if a word was more suitable for describing people or objects while ignoring a task-irrelevant image, and showed faster responses if the words and the unfamiliar objects were congruent in terms of animacy (e.g., animal-like objects with words that described human). Participants then learned to associate objects and words that were either congruent or not in animacy, before receiving expertise training to rapidly individuate the objects. Congruent pairing of visual and conceptual information facilitated observers' ability to become a perceptual expert, as revealed in a matching task that required visual identification at the basic or subordinate levels. Taken together, these findings show that visual and conceptual information interact at multiple levels in object recognition. PMID:25120509

  8. The role of the dorsal dentate gyrus in object and object-context recognition.

    PubMed

    Dees, Richard L; Kesner, Raymond P

    2013-11-01

    The aim of this study was to determine the role of the dorsal dentate gyrus (dDG) in object recognition memory using a black box and object-context recognition memory using a clear box with available cues that define a spatial context. Based on a 10 min retention interval between the study phase and the test phase, the results indicated that dDG lesioned rats are impaired when compared to controls in the object-context recognition test in the clear box. However, there were no reliable differences between the dDG lesioned rats and the control group for the object recognition test in the black box. Even though the dDG lesioned rats were more active in object exploration, the habituation gradients did not differ. These results suggest that the dentate gyrus lesioned rats are clearly impaired when there is an important contribution of context. Furthermore, based on a 24 h retention interval in the black box the dDG lesioned rats were impaired compared to controls. PMID:23880567

  9. The limits of feedforward vision: recurrent processing promotes robust object recognition when objects are degraded.

    PubMed

    Wyatte, Dean; Curran, Tim; O'Reilly, Randall

    2012-11-01

    Everyday vision requires robustness to a myriad of environmental factors that degrade stimuli. Foreground clutter can occlude objects of interest, and complex lighting and shadows can decrease the contrast of items. How does the brain recognize visual objects despite these low-quality inputs? On the basis of predictions from a model of object recognition that contains excitatory feedback, we hypothesized that recurrent processing would promote robust recognition when objects were degraded by strengthening bottom-up signals that were weakened because of occlusion and contrast reduction. To test this hypothesis, we used backward masking to interrupt the processing of partially occluded and contrast reduced images during a categorization experiment. As predicted by the model, we found significant interactions between the mask and occlusion and the mask and contrast, such that the recognition of heavily degraded stimuli was differentially impaired by masking. The model provided a close fit of these results in an isomorphic version of the experiment with identical stimuli. The model also provided an intuitive explanation of the interactions between the mask and degradations, indicating that masking interfered specifically with the extensive recurrent processing necessary to amplify and resolve highly degraded inputs, whereas less degraded inputs did not require much amplification and could be rapidly resolved, making them less susceptible to masking. Together, the results of the experiment and the accompanying model simulations illustrate the limits of feedforward vision and suggest that object recognition is better characterized as a highly interactive, dynamic process that depends on the coordination of multiple brain areas. PMID:22905822

  10. Object recognition by triaural perception on a mobile robot

    NASA Astrophysics Data System (ADS)

    Peremans, Herbert; Van Campenhout, Jan M.

    1993-05-01

    To overcome some of the problems associated with the use of ultrasonic sensors for navigation purposes, we propose a measurement system composed of three ultrasonic sensors, one transmitting and three receiving, placed on a moving vehicle. By triangulation this tri-aural sensor is able to determine the position, both distance and bearing, of the objects in the field of view. In this paper, we derive a statistical test which combines consecutive sightings by the moving sensor, of the same object to determine whether it is an edge, a plane or a corner. This test is formulated as a sequential test which guarantees that the object will be recognized after the minimal number of measurements given predetermined error probabilities. We include experimental data showing the object recognition capabilities of the system.

  11. 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

  12. Picture-object recognition in the tortoise Chelonoidis carbonaria.

    PubMed

    Wilkinson, Anna; Mueller-Paul, Julia; Huber, Ludwig

    2013-01-01

    To recognize that a picture is a representation of a real-life object is a cognitively demanding task. It requires an organism to mentally represent the concrete object (the picture) and abstract its relation to the item that it represents. This form of representational insight has been shown in a small number of mammal and bird species. However, it has not previously been studied in reptiles. This study examined picture-object recognition in the red-footed tortoise (Chelonoidis carbonaria). In Experiment 1, five red-footed tortoises were trained to distinguish between food and non-food objects using a two-alternative forced choice procedure. After reaching criterion, they were presented with test trials in which the real objects were replaced with color photographs of those objects. There was no difference in performance between training and test trials, suggesting that the tortoises did see some correspondence between the real object and its photographic representation. Experiment 2 examined the nature of this correspondence by presenting the tortoises with a choice between the real food object and a photograph of it. The findings revealed that the tortoises confused the photograph with the real-life object. This suggests that they process real items and photographic representations of these items in the same way and, in this context, do not exhibit representational insight. PMID:22945433

  13. 3D shape and eccentricity measurements of fast rotating rough objects by two mutually tilted interference fringe systems

    NASA Astrophysics Data System (ADS)

    Czarske, J. W.; Kuschmierz, R.; Günther, P.

    2013-06-01

    Precise measurements of distance, eccentricity and 3D-shape of fast moving objects such as turning parts of lathes, gear shafts, magnetic bearings, camshafts, crankshafts and rotors of vacuum pumps are on the one hand important tasks. On the other hand they are big challenges, since contactless precise measurement techniques are required. Optical techniques are well suitable for distance measurements of non-moving surfaces. However, measurements of laterally fast moving surfaces are still challenging. For such tasks the laser Doppler distance sensor technique was invented by the TU Dresden some years ago. This technique has been realized by two mutually tilted interference fringe systems, where the distance is coded in the phase difference between the generated interference signals. However, due to the speckle effect different random envelopes and phase jumps of the interference signals occur. They disturb the phase difference estimation between the interference signals. In this paper, we will report on a scientific breakthrough on the measurement uncertainty budget which has been achieved recently. Via matching of the illumination and receiving optics the measurement uncertainty of the displacement and distance can be reduced by about one magnitude. For displacement measurements of a recurring rough surface a standard deviation of 110 nm were attained at lateral velocities of 5 m / s. Due to the additionally measured lateral velocity and the rotational speed, the two-dimensional shape of rotating objects is calculated. The three-dimensional shape can be conducted by employment of a line camera. Since the measurement uncertainty of the displacement, vibration, distance, eccentricity, and shape is nearly independent of the lateral surface velocity, this technique is predestined for fast-rotating objects. Especially it can be advantageously used for the quality control of workpieces inside of a lathe towards the reduction of process tolerances, installation times and

  14. Determinants of novel object and location recognition during development.

    PubMed

    Jablonski, S A; Schreiber, W B; Westbrook, S R; Brennan, L E; Stanton, M E

    2013-11-01

    In the novel object recognition (OR) paradigm, rats are placed in an arena where they encounter two sample objects during a familiarization phase. A few minutes later, they are returned to the same arena and are presented with a familiar object and a novel object. The object location recognition (OL) variant involves the same familiarization procedure but during testing one of the familiar objects is placed in a novel location. Normal adult rats are able to perform both the OR and OL tasks, as indicated by enhanced exploration of the novel vs. the familiar test item. Rats with hippocampal lesions perform the OR but not OL task indicating a role of spatial memory in OL. Recently, these tasks have been used to study the ontogeny of spatial memory but the literature has yielded conflicting results. The current experiments add to this literature by: (1) behaviorally characterizing these paradigms in postnatal day (PD) 21, 26 and 31-day-old rats; (2) examining the role of NMDA systems in OR vs. OL; and (3) investigating the effects of neonatal alcohol exposure on both tasks. Results indicate that normal-developing rats are able to perform OR and OL by PD21, with greater novelty exploration in the OR task at each age. Second, memory acquisition in the OL but not OR task requires NMDA receptor function in juvenile rats [corrected]. Lastly, neonatal alcohol exposure does not disrupt performance in either task. Implications for the ontogeny of incidental spatial learning and its disruption by developmental alcohol exposure are discussed. PMID:23933466

  15. 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

  16. Random neural network recognition of shaped objects in strong clutter

    NASA Astrophysics Data System (ADS)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-04-01

    Detecting objects in images containing strong clutter is an important issue in a variety of applications such as medical imaging and automatic target recognition. Artificial neural networks are used as non-parametric pattern recognizers to cope with different problems due to their inherent ability to learn from training data. In this paper we propose a neural approach based on the Random Neural Network model (Gelenbe 1989, 1990, 1991, 1993), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.

  17. Visual discrimination of rotated 3D objects in Malawi cichlids (Pseudotropheus sp.): a first indication for form constancy in fishes.

    PubMed

    Schluessel, V; Kraniotakes, H; Bleckmann, H

    2014-03-01

    Fish move in a three-dimensional environment in which it is important to discriminate between stimuli varying in colour, size, and shape. It is also advantageous to be able to recognize the same structures or individuals when presented from different angles, such as back to front or front to side. This study assessed visual discrimination abilities of rotated three-dimensional objects in eight individuals of Pseudotropheus sp. using various plastic animal models. All models were displayed in two choice experiments. After successful training, fish were presented in a range of transfer tests with objects rotated in the same plane and in space by 45° and 90° to the side or to the front. In one experiment, models were additionally rotated by 180°, i.e., shown back to front. Fish showed quick associative learning and with only one exception successfully solved and finished all experimental tasks. These results provide first evidence for form constancy in this species and in fish in general. Furthermore, Pseudotropheus seemed to be able to categorize stimuli; a range of turtle and frog models were recognized independently of colour and minor shape variations. Form constancy and categorization abilities may be important for behaviours such as foraging, recognition of predators, and conspecifics as well as for orienting within habitats or territories. PMID:23982620

  18. Object-constrained meshless deformable algorithm for high speed 3D nonrigid registration between CT and CBCT

    SciTech Connect

    Chen Ting; Kim, Sung; Goyal, Sharad; Jabbour, Salma; Zhou Jinghao; Rajagopal, Gunaretnum; Haffty, Bruce; Yue Ning

    2010-01-15

    Purpose: High-speed nonrigid registration between the planning CT and the treatment CBCT data is critical for real time image guided radiotherapy (IGRT) to improve the dose distribution and to reduce the toxicity to adjacent organs. The authors propose a new fully automatic 3D registration framework that integrates object-based global and seed constraints with the grayscale-based ''demons'' algorithm. Methods: Clinical objects were segmented on the planning CT images and were utilized as meshless deformable models during the nonrigid registration process. The meshless models reinforced a global constraint in addition to the grayscale difference between CT and CBCT in order to maintain the shape and the volume of geometrically complex 3D objects during the registration. To expedite the registration process, the framework was stratified into hierarchies, and the authors used a frequency domain formulation to diffuse the displacement between the reference and the target in each hierarchy. Also during the registration of pelvis images, they replaced the air region inside the rectum with estimated pixel values from the surrounding rectal wall and introduced an additional seed constraint to robustly track and match the seeds implanted into the prostate. The proposed registration framework and algorithm were evaluated on 15 real prostate cancer patients. For each patient, prostate gland, seminal vesicle, bladder, and rectum were first segmented by a radiation oncologist on planning CT images for radiotherapy planning purpose. The same radiation oncologist also manually delineated the tumor volumes and critical anatomical structures in the corresponding CBCT images acquired at treatment. These delineated structures on the CBCT were only used as the ground truth for the quantitative validation, while structures on the planning CT were used both as the input to the registration method and the ground truth in validation. By registering the planning CT to the CBCT, a

  19. Factor G utilizes a carbohydrate-binding cleft that is conserved between horseshoe crab and bacteria for the recognition of beta-1,3-D-glucans.

    PubMed

    Ueda, Yuki; Ohwada, Shuhei; Abe, Yoshito; Shibata, Toshio; Iijima, Manabu; Yoshimitsu, Yukiko; Koshiba, Takumi; Nakata, Munehiro; Ueda, Tadashi; Kawabata, Shun-ichiro

    2009-09-15

    In the horseshoe crab, the recognition of beta-1,3-D-glucans by factor G triggers hemolymph coagulation. Factor G contains a domain of two tandem xylanase Z-like modules (Z1-Z2), each of which recognizes beta-1,3-D-glucans. To gain an insight into the recognition of beta-1,3-D-glucans from a structural view point, recombinants of Z1-Z2, the C-terminal module Z2, Z2 with a Cys to Ala substitution (Z2A), and its tandem repeat Z2A-Z2A were characterized. Z2 and Z1-Z2, but not Z2A and Z2A-Z2A, formed insoluble aggregates at higher concentrations more than approximately 30 and 3 microM, respectively. Z1-Z2 and Z2A-Z2A bound more strongly to an insoluble beta-1,3-D-glucan (curdlan) than Z2A. The affinity of Z2A for a soluble beta-1,3-D-glucan (laminarin) was equivalent to those of Z1-Z2, Z2A-Z2A, and native factor G, suggesting that the binding of a single xylanase Z-like module prevents the subsequent binding of another module to laminarin. Interestingly, Z2A as well as intact factor G exhibited fungal agglutinating activity, and fungi were specifically detected with fluorescently tagged Z2A by microscopy. The chemical shift perturbation of Z2A induced by the interaction with laminaripentaose was analyzed by nuclear magnetic resonance spectroscopy. The ligand-binding site of Z2A was located in a cleft on a beta-sheet in a predicted beta-sandwich structure, which was superimposed onto cleft B in a cellulose-binding module of endoglucanase 5A from the soil bacterium Cellvibrio mixtus. We conclude that the pattern recognition for beta-1,3-D-glucans by factor G is accomplished via a carbohydrate-binding cleft that is evolutionally conserved between horseshoe crab and bacteria. PMID:19710471

  20. Europeana and 3D

    NASA Astrophysics Data System (ADS)

    Pletinckx, D.

    2011-09-01

    The current 3D hype creates a lot of interest in 3D. People go to 3D movies, but are we ready to use 3D in our homes, in our offices, in our communication? Are we ready to deliver real 3D to a general public and use interactive 3D in a meaningful way to enjoy, learn, communicate? The CARARE project is realising this for the moment in the domain of monuments and archaeology, so that real 3D of archaeological sites and European monuments will be available to the general public by 2012. There are several aspects to this endeavour. First of all is the technical aspect of flawlessly delivering 3D content over all platforms and operating systems, without installing software. We have currently a working solution in PDF, but HTML5 will probably be the future. Secondly, there is still little knowledge on how to create 3D learning objects, 3D tourist information or 3D scholarly communication. We are still in a prototype phase when it comes to integrate 3D objects in physical or virtual museums. Nevertheless, Europeana has a tremendous potential as a multi-facetted virtual museum. Finally, 3D has a large potential to act as a hub of information, linking to related 2D imagery, texts, video, sound. We describe how to create such rich, explorable 3D objects that can be used intuitively by the generic Europeana user and what metadata is needed to support the semantic linking.

  1. Declining object recognition performance in semantic dementia: A case for stored visual object representations.

    PubMed

    Tree, Jeremy J; Playfoot, David

    2015-01-01

    The role of the semantic system in recognizing objects is a matter of debate. Connectionist theories argue that it is impossible for a participant to determine that an object is familiar to them without recourse to a semantic hub; localist theories state that accessing a stored representation of the visual features of the object is sufficient for recognition. We examine this issue through the longitudinal study of two cases of semantic dementia, a neurodegenerative disorder characterized by a progressive degradation of the semantic system. The cases in this paper do not conform to the "common" pattern of object recognition performance in semantic dementia described by Rogers, T. T., Lambon Ralph, M. A., Hodges, J. R., & Patterson, K. (2004). Natural selection: The impact of semantic impairment on lexical and object decision. Cognitive Neuropsychology, 21, 331-352., and show no systematic relationship between severity of semantic impairment and success in object decision. We argue that these data are inconsistent with the connectionist position but can be easily reconciled with localist theories that propose stored structural descriptions of objects outside of the semantic system. PMID:27355607

  2. 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

  3. 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.

  4. The role of color in expert object recognition.

    PubMed

    Hagen, Simen; Vuong, Quoc C; Scott, Lisa S; Curran, Tim; Tanaka, James W

    2014-01-01

    In the current study, we examined how color knowledge in a domain of expertise influences the accuracy and speed of object recognition. In Experiment 1, expert bird-watchers and novice participants categorized common birds (e.g., robin, sparrow, cardinal) at the family level of abstraction. The bird images were shown in their natural congruent color, nonnatural incongruent color, and gray scale. The main finding was that color affected the performance of bird experts and bird novices, albeit in different ways. Although both experts and novices relied on color to recognize birds at the family level, analysis of the response time distribution revealed that color facilitated expert performance in the fastest and slowest trials whereas color only helped the novices in the slower trials. In Experiment 2, expert bird-watchers were asked to categorize congruent color, incongruent color, and gray scale images of birds at the more subordinate, species level (e.g., Nashville warbler, Wilson's warbler). The performance of experts was better with congruent color images than with incongruent color and gray scale images. As in Experiment 1, analysis of the response time distribution showed that the color effect was present in the fastest trials and was sustained through the slowest trials. Collectively, the findings show that experts have ready access to color knowledge that facilitates their fast and accurate identification at the family and species level of recognition. PMID:25113021

  5. A computational model that recovers the 3D shape of an object from a single 2D retinal representation.

    PubMed

    Li, Yunfeng; Pizlo, Zygmunt; Steinman, Robert M

    2009-05-01

    Human beings perceive 3D shapes veridically, but the underlying mechanisms remain unknown. The problem of producing veridical shape percepts is computationally difficult because the 3D shapes have to be recovered from 2D retinal images. This paper describes a new model, based on a regularization approach, that does this very well. It uses a new simplicity principle composed of four shape constraints: viz., symmetry, planarity, maximum compactness and minimum surface. Maximum compactness and minimum surface have never been used before. The model was tested with random symmetrical polyhedra. It recovered their 3D shapes from a single randomly-chosen 2D image. Neither learning, nor depth perception, was required. The effectiveness of the maximum compactness and the minimum surface constraints were measured by how well the aspect ratio of the 3D shapes was recovered. These constraints were effective; they recovered the aspect ratio of the 3D shapes very well. Aspect ratios recovered by the model were compared to aspect ratios adjusted by four human observers. They also adjusted aspect ratios very well. In those rare cases, in which the human observers showed large errors in adjusted aspect ratios, their errors were very similar to the errors made by the model. PMID:18621410

  6. 3-D SAR image formation from sparse aperture data using 3-D target grids

    NASA Astrophysics Data System (ADS)

    Bhalla, Rajan; Li, Junfei; Ling, Hao

    2005-05-01

    The performance of ATR systems can potentially be improved by using three-dimensional (3-D) SAR images instead of the traditional two-dimensional SAR images or one-dimensional range profiles. 3-D SAR image formation of targets from radar backscattered data collected on wide angle, sparse apertures has been identified by AFRL as fundamental to building an object detection and recognition capability. A set of data has been released as a challenge problem. This paper describes a technique based on the concept of 3-D target grids aimed at the formation of 3-D SAR images of targets from sparse aperture data. The 3-D target grids capture the 3-D spatial and angular scattering properties of the target and serve as matched filters for SAR formation. The results of 3-D SAR formation using the backhoe public release data are presented.

  7. 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.

  8. 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

  9. A model for calculating the errors of 2D bulk analysis relative to the true 3D bulk composition of an object, with application to chondrules

    NASA Astrophysics Data System (ADS)

    Hezel, Dominik C.

    2007-09-01

    Certain problems in Geosciences require knowledge of the chemical bulk composition of objects, such as, for example, minerals or lithic clasts. This 3D bulk chemical composition (bcc) is often difficult to obtain, but if the object is prepared as a thin or thick polished section a 2D bcc can be easily determined using, for example, an electron microprobe. The 2D bcc contains an error relative to the true 3D bcc that is unknown. Here I present a computer program that calculates this error, which is represented as the standard deviation of the 2D bcc relative to the real 3D bcc. A requirement for such calculations is an approximate structure of the 3D object. In petrological applications, the known fabrics of rocks facilitate modeling. The size of the standard deviation depends on (1) the modal abundance of the phases, (2) the element concentration differences between phases and (3) the distribution of the phases, i.e. the homogeneity/heterogeneity of the object considered. A newly introduced parameter " τ" is used as a measure of this homogeneity/heterogeneity. Accessory phases, which do not necessarily appear in 2D thin sections, are a second source of error, in particular if they contain high concentrations of specific elements. An abundance of only 1 vol% of an accessory phase may raise the 3D bcc of an element by up to a factor of ˜8. The code can be queried as to whether broad beam, point, line or area analysis technique is best for obtaining 2D bcc. No general conclusion can be deduced, as the error rates of these techniques depend on the specific structure of the object considered. As an example chondrules—rapidly solidified melt droplets of chondritic meteorites—are used. It is demonstrated that 2D bcc may be used to reveal trends in the chemistry of 3D objects.

  10. Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

    NASA Technical Reports Server (NTRS)

    Schenker, Paul S. (Editor)

    1991-01-01

    The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

  11. 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

  12. 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.

  13. 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.

  14. 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. PMID:26807789

  15. Object recognition in Williams syndrome: Uneven ventral stream activation

    PubMed Central

    O’Hearn, Kirsten; Roth, Jennifer K.; Courtney, Susan M.; Luna, Beatriz; Street, Whitney; Terwillinger, Robert; Landau, Barbara

    2010-01-01

    Williams syndrome (WS) is a genetic disorder associated with severe visuospatial deficits, relatively strong language skills, heightened social interest, and increased attention to faces. On the basis of the visuospatial impairments, this disorder has been characterized primarily as a deficit of the dorsal stream, the occipitoparietal brain regions that subserve visuospatial processing. However, some evidence indicates that this disorder may also affect the development of the ventral stream, the occipitotemporal cortical regions that subserve face and object recognition. The present studies examined ventral stream function in WS, with the hypothesis that faces would produce a relatively more mature pattern of ventral occipitotemporal cortical activation, relative to other objects that are also represented across these visual areas. We compared functional magnetic resonance imaging activation patterns during viewing of human faces, cat faces, houses and shoes in individuals with WS (age 14–27), typically developing 6–9 year olds (matched approximately on mental age), and typically developing 14–26 year olds (matched on chronological age). Typically developing individuals exhibited changes in the pattern of activation over age, consistent with previous reports. The ventral stream topography of the WS individuals differed from both control groups, however, reflecting the same level of activation to face stimuli as chronological age matches, but less activation to house stimuli than either mental age or chronological age matches. We discuss the possible causes of this unusual topography and implications for understanding the behavioral profile of people with WS. PMID:21477194

  16. High-speed correspondence for object recognition and tracking

    NASA Astrophysics Data System (ADS)

    Ariyawansa, Dambakumbure D.; Clarke, Timothy A.

    1997-07-01

    Real-time measurement using multi-camera 3D measuring system requires three major components to operate at high speed: image data processing; correspondence; and least squares estimation. This paper is based upon a system developed at City University which uses high speed solutions for the first and last elements, and describes recent work to provide a high speed solution to the correspondence problem. Correspondence has traditionally been solved in photogrammetry by using human stereo fusion of two views of an object providing an immediate solution. Computer vision researchers and photogrammetrists have applied image processing techniques and computers to the same configuration and have developed numerous matching algorithms with considerable success. Where research is still required, and the published work is not so plentiful, is in the area of multi-camera correspondence. The most commonly used methods utilize the epipolar geometry to establish the correspondences. While this method is adequate for some simple situations, extensions to more than just a few cameras are required which are reliable and efficient. In this paper the early stages of research into reliable and efficient multi-camera correspondence method for high speed measurement tasks are reported.

  17. EM modelling of arbitrary shaped anisotropic dielectric objects using an efficient 3D leapfrog scheme on unstructured meshes

    NASA Astrophysics Data System (ADS)

    Gansen, A.; Hachemi, M. El; Belouettar, S.; Hassan, O.; Morgan, K.

    2016-09-01

    The standard Yee algorithm is widely used in computational electromagnetics because of its simplicity and divergence free nature. A generalization of the classical Yee scheme to 3D unstructured meshes is adopted, based on the use of a Delaunay primal mesh and its high quality Voronoi dual. This allows the problem of accuracy losses, which are normally associated with the use of the standard Yee scheme and a staircased representation of curved material interfaces, to be circumvented. The 3D dual mesh leapfrog-scheme which is presented has the ability to model both electric and magnetic anisotropic lossy materials. This approach enables the modelling of problems, of current practical interest, involving structured composites and metamaterials.

  18. 3D micro-XRF for cultural heritage objects: new analysis strategies for the investigation of the Dead Sea Scrolls.

    PubMed

    Mantouvalou, Ioanna; Wolff, Timo; Hahn, Oliver; Rabin, Ira; Lühl, Lars; Pagels, Marcel; Malzer, Wolfgang; Kanngiesser, Birgit

    2011-08-15

    A combination of 3D micro X-ray fluorescence spectroscopy (3D micro-XRF) and micro-XRF was utilized for the investigation of a small collection of highly heterogeneous, partly degraded Dead Sea Scroll parchment samples from known excavation sites. The quantitative combination of the two techniques proves to be suitable for the identification of reliable marker elements which may be used for classification and provenance studies. With 3D micro-XRF, the three-dimensional nature, i.e. the depth-resolved elemental composition as well as density variations, of the samples was investigated and bromine could be identified as a suitable marker element. It is shown through a comparison of quantitative and semiquantitative values for the bromine content derived using both techniques that, for elements which are homogeneously distributed in the sample matrix, quantification with micro-XRF using a one-layer model is feasible. Thus, the possibility for routine provenance studies using portable micro-XRF instrumentation on a vast amount of samples, even on site, is obtained through this work. PMID:21711051

  19. Preliminary study of statistical pattern recognition-based coin counterfeit detection by means of high resolution 3D scanners

    NASA Astrophysics Data System (ADS)

    Leich, Marcus; Kiltz, Stefan; Krätzer, Christian; Dittmann, Jana; Vielhauer, Claus

    2011-03-01

    According to the European Commission around 200,000 counterfeit Euro coins are removed from circulation every year. While approaches exist to automatically detect these coins, satisfying error rates are usually only reached for low quality forgeries, so-called "local classes". High-quality minted forgeries ("common classes") pose a problem for these methods as well as for trained humans. This paper presents a first approach for statistical analysis of coins based on high resolution 3D data acquired with a chromatic white light sensor. The goal of this analysis is to determine whether two coins are of common origin. The test set for these first and new investigations consists of 62 coins from not more than five different sources. The analysis is based on the assumption that, apart from markings caused by wear such as scratches and residue consisting of grease and dust, coins from equal origin have a more similar height field than coins from different mints. First results suggest that the selected approach is heavily affected by influences of wear like dents and scratches and the further research is required the eliminate this influence. A course for future work is outlined.

  20. 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.

  1. Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

    PubMed Central

    Kosik, Ivan; Raess, Avery

    2015-01-01

    Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

  2. Modeling of 3-D Object Manipulation by Multi-Joint Robot Fingers under Non-Holonomic Constraints and Stable Blind Grasping

    NASA Astrophysics Data System (ADS)

    Arimoto, Suguru; Yoshida, Morio; Bae, Ji-Hun

    This paper derives a mathematical model that expresses motion of a pair of multi-joint robot fingers with hemi-spherical rigid ends grasping and manipulating a 3-D rigid object with parallel flat surfaces. Rolling contacts arising between finger-ends and object surfaces are taken into consideration and modeled as Pfaffian constraints from which constraint forces emerge tangentially to the object surfaces. Another noteworthy difference of modeling of motion of a 3-D object from that of a 2-D object is that the instantaneous axis of rotation of the object is fixed in the 2-D case but that is time-varying in the 3-D case. A further difficulty that has prevented us to model 3-D physical interactions between a pair of fingers and a rigid object lies in the problem of treating spinning motion that may arise around the opposing axis from a contact point between one finger-end with one side of the object to another contact point. This paper shows that, once such spinning motion stops as the object mass center approaches just beneath the opposition axis, then this cease of spinning evokes a further nonholonomic constraint. Hence, the multi-body dynamics of the overall fingers-object system is subject to non-holonomic constraints concerning a 3-D orthogonal matrix expressing three mutually orthogonal unit vectors fixed at the object together with an extra non-holonomic constraint that the instantaneous axis of rotation of the object is always orthogonal to the opposing axis. It is shown that Lagrange's equation of motion of the overall system can be derived without violating the causality that governs the non-holonomic constraints. This immediately suggests possible construction of a numerical simulator of multi-body dynamics that can express motion of the fingers and object physically interactive to each other. By referring to the fact that human grasp an object in the form of precision prehension dynamically and stably by using opposable force between the thumb and another

  3. Poka Yoke system based on image analysis and object recognition

    NASA Astrophysics Data System (ADS)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  4. Crowding, grouping, and object recognition: A matter of appearance

    PubMed Central

    Herzog, Michael H.; Sayim, Bilge; Chicherov, Vitaly; Manassi, Mauro

    2015-01-01

    In crowding, the perception of a target strongly deteriorates when neighboring elements are presented. Crowding is usually assumed to have the following characteristics. (a) Crowding is determined only by nearby elements within a restricted region around the target (Bouma's law). (b) Increasing the number of flankers can only deteriorate performance. (c) Target-flanker interference is feature-specific. These characteristics are usually explained by pooling models, which are well in the spirit of classic models of object recognition. In this review, we summarize recent findings showing that crowding is not determined by the above characteristics, thus, challenging most models of crowding. We propose that the spatial configuration across the entire visual field determines crowding. Only when one understands how all elements of a visual scene group with each other, can one determine crowding strength. We put forward the hypothesis that appearance (i.e., how stimuli look) is a good predictor for crowding, because both crowding and appearance reflect the output of recurrent processing rather than interactions during the initial phase of visual processing. PMID:26024452

  5. An analysis of TA-Student Interaction and the Development of Concepts in 3-d Space Through Language, Objects, and Gesture in a College-level Geoscience Laboratory

    NASA Astrophysics Data System (ADS)

    King, S. L.

    2015-12-01

    The purpose of this study is twofold: 1) to describe how a teaching assistant (TA) in an undergraduate geology laboratory employs a multimodal system in order to mediate the students' understanding of scientific knowledge and develop a contextualization of a concept in three-dimensional space and 2) to describe how a linguistic awareness of gestural patterns can be used to inform TA training assessment of students' conceptual understanding in situ. During the study the TA aided students in developing the conceptual understanding and reconstruction of a meteoric impact, which produces shatter cone formations. The concurrent use of speech, gesture, and physical manipulation of objects is employed by the TA in order to aid the conceptual understanding of this particular phenomenon. Using the methods of gestural analysis in works by Goldin-Meadow, 2000 and McNeill, 1992, this study describes the gestures of the TA and the students as well as the purpose and motivation of the meditational strategies employed by TA in order to build the geological concept in the constructed 3-dimensional space. Through a series of increasingly complex gestures, the TA assists the students to construct the forensic concept of the imagined 3-D space, which can then be applied to a larger context. As the TA becomes more familiar with the students' meditational needs, the TA adapts teaching and gestural styles to meet their respective ZPDs (Vygotsky 1978). This study shows that in the laboratory setting language, gesture, and physical manipulation of the experimental object are all integral to the learning and demonstration of scientific concepts. Recognition of the gestural patterns of the students allows the TA the ability to dynamically assess the students understanding of a concept. Using the information from this example of student-TA interaction, a brief short course has been created to assist TAs in recognizing the mediational power as well as the assessment potential of gestural

  6. Similarity dependency of the change in ERP component N1 accompanying with the object recognition learning.

    PubMed

    Tokudome, Wataru; Wang, Gang

    2012-01-01

    Performance during object recognition across views is largely dependent on inter-object similarity. The present study was designed to investigate the similarity dependency of object recognition learning on the changes in ERP component N1. Human subjects were asked to train themselves to recognize novel objects with different inter-object similarity by performing object recognition tasks. During the tasks, images of an object had to be discriminated from the images of other objects irrespective of the viewpoint. When objects had a high inter-object similarity, the ERP component, N1 exhibited a significant increase in both the amplitude and the latency variation across objects during the object recognition learning process, and the N1 amplitude and latency variation across the views of the same objects decreased significantly. In contrast, no significant changes were found during the learning process when using objects with low inter-object similarity. The present findings demonstrate that the changes in the variation of N1 that accompany the object recognition learning process are dependent upon the inter-object similarity and imply that there is a difference in the neuronal representation for object recognition when using objects with high and low inter-object similarity. PMID:22115890

  7. 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

  8. Scopolamine infused into perirhinal cortex improves object recognition memory by blocking the acquisition of interfering object information

    PubMed Central

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

    2007-01-01

    In a previous study, we reported apparently paradoxical facilitation of object recognition memory following infusions of the cholinergic muscarinic receptor antagonist scopolamine into the perirhinal cortex (PRh) of rats. We attributed these effects to the blockade by scopolamine of the acquisition of interfering information. The present study tested this possibility directly by modifying the spontaneous object recognition memory task to allow the presentation of a potentially interfering object either before the sample phase or in the retention delay between the sample and choice phases. Presentation of an object between the sample and choice phases disrupted subsequent recognition of the sample object (retroactive interference), and intra-PRh infusions of scopolamine prior to the presentation of the irrelevant object prevented this retroactive interference effect. Moreover, presentation of an irrelevant object prior to the sample phase interfered proactively with sample object recognition, and intra-PRh infusions of scopolamine prior to the presentation of the pre-sample object prevented this proactive interference effect. These results suggest that blocking muscarinic cholinergic receptors in PRh can disrupt the acquisition of potentially interfering object information, thereby facilitating object recognition memory. This finding provides further, strong evidence that acetylcholine is important for the acquisition of object information in PRh. PMID:17823242

  9. Research into a Single-aperture Light Field Camera System to Obtain Passive Ground-based 3D Imagery of LEO Objects

    NASA Astrophysics Data System (ADS)

    Bechis, K.; Pitruzzello, A.

    2014-09-01

    This presentation describes our ongoing research into using a ground-based light field camera to obtain passive, single-aperture 3D imagery of LEO objects. Light field cameras are an emerging and rapidly evolving technology for passive 3D imaging with a single optical sensor. The cameras use an array of lenslets placed in front of the camera focal plane, which provides angle of arrival information for light rays originating from across the target, allowing range to target and 3D image to be obtained from a single image using monocular optics. The technology, which has been commercially available for less than four years, has the potential to replace dual-sensor systems such as stereo cameras, dual radar-optical systems, and optical-LIDAR fused systems, thus reducing size, weight, cost, and complexity. We have developed a prototype system for passive ranging and 3D imaging using a commercial light field camera and custom light field image processing algorithms. Our light field camera system has been demonstrated for ground-target surveillance and threat detection applications, and this paper presents results of our research thus far into applying this technology to the 3D imaging of LEO objects. The prototype 3D imaging camera system developed by Northrop Grumman uses a Raytrix R5 C2GigE light field camera connected to a Windows computer with an nVidia graphics processing unit (GPU). The system has a frame rate of 30 Hz, and a software control interface allows for automated camera triggering and light field image acquisition to disk. Custom image processing software then performs the following steps: (1) image refocusing, (2) change detection, (3) range finding, and (4) 3D reconstruction. In Step (1), a series of 2D images are generated from each light field image; the 2D images can be refocused at up to 100 different depths. Currently, steps (1) through (3) are automated, while step (4) requires some user interaction. A key requirement for light field camera

  10. 3D tracking of single nanoparticles and quantum dots in living cells by out-of-focus imaging with diffraction pattern recognition

    NASA Astrophysics Data System (ADS)

    Gardini, Lucia; Capitanio, Marco; Pavone, Francesco S.

    2015-11-01

    Live cells are three-dimensional environments where biological molecules move to find their targets and accomplish their functions. However, up to now, most single molecule investigations have been limited to bi-dimensional studies owing to the complexity of 3d-tracking techniques. Here, we present a novel method for three-dimensional localization of single nano-emitters based on automatic recognition of out-of-focus diffraction patterns. Our technique can be applied to track the movements of single molecules in living cells using a conventional epifluorescence microscope. We first demonstrate three-dimensional localization of fluorescent nanobeads over 4 microns depth with accuracy below 2 nm in vitro. Remarkably, we also establish three-dimensional tracking of Quantum Dots, overcoming their anisotropic emission, by adopting a ligation strategy that allows rotational freedom of the emitter combined with proper pattern recognition. We localize commercially available Quantum Dots in living cells with accuracy better than 7 nm over 2 microns depth. We validate our technique by tracking the three-dimensional movements of single protein-conjugated Quantum Dots in living cell. Moreover, we find that important localization errors can occur in off-focus imaging when improperly calibrated and we give indications to avoid them. Finally, we share a Matlab script that allows readily application of our technique by other laboratories.

  11. 3D tracking of single nanoparticles and quantum dots in living cells by out-of-focus imaging with diffraction pattern recognition

    PubMed Central

    Gardini, Lucia; Capitanio, Marco; Pavone, Francesco S.

    2015-01-01

    Live cells are three-dimensional environments where biological molecules move to find their targets and accomplish their functions. However, up to now, most single molecule investigations have been limited to bi-dimensional studies owing to the complexity of 3d-tracking techniques. Here, we present a novel method for three-dimensional localization of single nano-emitters based on automatic recognition of out-of-focus diffraction patterns. Our technique can be applied to track the movements of single molecules in living cells using a conventional epifluorescence microscope. We first demonstrate three-dimensional localization of fluorescent nanobeads over 4 microns depth with accuracy below 2 nm in vitro. Remarkably, we also establish three-dimensional tracking of Quantum Dots, overcoming their anisotropic emission, by adopting a ligation strategy that allows rotational freedom of the emitter combined with proper pattern recognition. We localize commercially available Quantum Dots in living cells with accuracy better than 7 nm over 2 microns depth. We validate our technique by tracking the three-dimensional movements of single protein-conjugated Quantum Dots in living cell. Moreover, we find that important localization errors can occur in off-focus imaging when improperly calibrated and we give indications to avoid them. Finally, we share a Matlab script that allows readily application of our technique by other laboratories. PMID:26526410

  12. 3D tracking of single nanoparticles and quantum dots in living cells by out-of-focus imaging with diffraction pattern recognition.

    PubMed

    Gardini, Lucia; Capitanio, Marco; Pavone, Francesco S

    2015-01-01

    Live cells are three-dimensional environments where biological molecules move to find their targets and accomplish their functions. However, up to now, most single molecule investigations have been limited to bi-dimensional studies owing to the complexity of 3d-tracking techniques. Here, we present a novel method for three-dimensional localization of single nano-emitters based on automatic recognition of out-of-focus diffraction patterns. Our technique can be applied to track the movements of single molecules in living cells using a conventional epifluorescence microscope. We first demonstrate three-dimensional localization of fluorescent nanobeads over 4 microns depth with accuracy below 2 nm in vitro. Remarkably, we also establish three-dimensional tracking of Quantum Dots, overcoming their anisotropic emission, by adopting a ligation strategy that allows rotational freedom of the emitter combined with proper pattern recognition. We localize commercially available Quantum Dots in living cells with accuracy better than 7 nm over 2 microns depth. We validate our technique by tracking the three-dimensional movements of single protein-conjugated Quantum Dots in living cell. Moreover, we find that important localization errors can occur in off-focus imaging when improperly calibrated and we give indications to avoid them. Finally, we share a Matlab script that allows readily application of our technique by other laboratories. PMID:26526410

  13. Fusion of multisensor passive and active 3D imagery

    NASA Astrophysics Data System (ADS)

    Fay, David A.; Verly, Jacques G.; Braun, Michael I.; Frost, Carl E.; Racamato, Joseph P.; Waxman, Allen M.

    2001-08-01

    We have extended our previous capabilities for fusion of multiple passive imaging sensors to now include 3D imagery obtained from a prototype flash ladar. Real-time fusion of low-light visible + uncooled LWIR + 3D LADAR, and SWIR + LWIR + 3D LADAR is demonstrated. Fused visualization is achieved by opponent-color neural networks for passive image fusion, which is then textured upon segmented object surfaces derived from the 3D data. An interactive viewer, coded in Java3D, is used to examine the 3D fused scene in stereo. Interactive designation, learning, recognition and search for targets, based on fused passive + 3D signatures, is achieved using Fuzzy ARTMAP neural networks with a Java-coded GUI. A client-server web-based architecture enables remote users to interact with fused 3D imagery via a wireless palmtop computer.

  14. It takes two-skilled recognition of objects engages lateral areas in both hemispheres.

    PubMed

    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

  15. 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

  16. Research on recognition methods of aphid objects in complex backgrounds

    NASA Astrophysics Data System (ADS)

    Zhao, Hui-Yan; Zhang, Ji-Hong

    2009-07-01

    In order to improve the recognition accuracy among the kinds of aphids in the complex backgrounds, the recognition method among kinds of aphids based on Dual-Tree Complex Wavelet Transform (DT-CWT) and Support Vector Machine (Libsvm) is proposed. Firstly the image is pretreated; secondly the aphid images' texture feature of three crops are extracted by DT-CWT in order to get the training parameters of training model; finally the training model could recognize aphids among the three kinds of crops. By contrasting to Gabor wavelet transform and the traditional extracting texture's methods based on Gray-Level Co-Occurrence Matrix (GLCM), the experiment result shows that the method has a certain practicality and feasibility and provides basic for aphids' recognition between the identification among same kind aphid.

  17. 3D and Education

    NASA Astrophysics Data System (ADS)

    Meulien Ohlmann, Odile

    2013-02-01

    Today the industry offers a chain of 3D products. Learning to "read" and to "create in 3D" becomes an issue of education of primary importance. 25 years professional experience in France, the United States and Germany, Odile Meulien set up a personal method of initiation to 3D creation that entails the spatial/temporal experience of the holographic visual. She will present some different tools and techniques used for this learning, their advantages and disadvantages, programs and issues of educational policies, constraints and expectations related to the development of new techniques for 3D imaging. Although the creation of display holograms is very much reduced compared to the creation of the 90ies, the holographic concept is spreading in all scientific, social, and artistic activities of our present time. She will also raise many questions: What means 3D? Is it communication? Is it perception? How the seeing and none seeing is interferes? What else has to be taken in consideration to communicate in 3D? How to handle the non visible relations of moving objects with subjects? Does this transform our model of exchange with others? What kind of interaction this has with our everyday life? Then come more practical questions: How to learn creating 3D visualization, to learn 3D grammar, 3D language, 3D thinking? What for? At what level? In which matter? for whom?

  18. Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

    PubMed

    Trelease, Robert B; Nieder, Gary L

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. PMID:23212750

  19. Infliximab ameliorates AD-associated object recognition memory impairment.

    PubMed

    Kim, Dong Hyun; Choi, Seong-Min; Jho, Jihoon; Park, Man-Seok; Kang, Jisu; Park, Se Jin; Ryu, Jong Hoon; Jo, Jihoon; Kim, Hyun Hee; Kim, Byeong C

    2016-09-15

    Dysfunctions in the perirhinal cortex (PRh) are associated with visual recognition memory deficit, which is frequently detected in the early stage of Alzheimer's disease. Muscarinic acetylcholine receptor-dependent long-term depression (mAChR-LTD) of synaptic transmission is known as a key pathway in eliciting this type of memory, and Tg2576 mice expressing enhanced levels of Aβ oligomers are found to have impaired mAChR-LTD in this brain area at as early as 3 months of age. We found that the administration of Aβ oligomers in young normal mice also induced visual recognition memory impairment and perturbed mAChR-LTD in mouse PRh slices. In addition, when mice were treated with infliximab, a monoclonal antibody against TNF-α, visual recognition memory impaired by pre-administered Aβ oligomers dramatically improved and the detrimental Aβ effect on mAChR-LTD was annulled. Taken together, these findings suggest that Aβ-induced inflammation is mediated through TNF-α signaling cascades, disturbing synaptic transmission in the PRh, and leading to visual recognition memory deficits. PMID:27265784

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

    PubMed

    Wood, Justin N; Wood, Samantha M W

    2016-04-27

    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

  1. 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…

  2. 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…

  3. X-ray 3D computed tomography of large objects: investigation of an ancient globe created by Vincenzo Coronelli

    NASA Astrophysics Data System (ADS)

    Morigi, Maria Pia; Casali, Franco; Berdondini, Andrea; Bettuzzi, Matteo; Bianconi, Davide; Brancaccio, Rosa; Castellani, Alice; D'Errico, Vincenzo; Pasini, Alessandro; Rossi, Alberto; Labanti, C.; Scianna, Nicolangelo

    2007-07-01

    X-ray cone-beam Computed Tomography is a powerful tool for the non-destructive investigation of the inner structure of works of art. With regard to Cultural Heritage conservation, different kinds of objects have to be inspected in order to acquire significant information such as the manufacturing technique or the presence of defects and damages. The knowledge of these features is very useful for determining adequate maintenance and restoration procedures. The use of medical CT scanners gives good results only when the investigated objects have size and density similar to those of the human body, however this requirement is not always fulfilled in Cultural Heritage diagnostics. For this reason a system for Digital Radiography and Computed Tomography of large objects, especially works of art, has been recently developed by researchers of the Physics Department of the University of Bologna. The design of the system is very different from any commercial available CT machine. The system consists of a 200 kVp X-ray source, a detector and a motorized mechanical structure for moving the detector and the object in order to collect the required number of radiographic projections. The detector is made up of a 450x450 mm2 structured CsI(Tl) scintillating screen, optically coupled to a CCD camera. In this paper we will present the results of the tomographic investigation recently performed on an ancient globe, created by the famous cosmographer, cartographer and encyclopedist Vincenzo Coronelli.

  4. Transforming Clinical Imaging and 3D Data for Virtual Reality Learning Objects: HTML5 and Mobile Devices Implementation

    ERIC Educational Resources Information Center

    Trelease, Robert B.; Nieder, Gary L.

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android…

  5. 3D-Modeling of deformed halite hopper crystals: Object based image analysis and support vector machine, a first evaluation

    NASA Astrophysics Data System (ADS)

    Leitner, Christoph; Hofmann, Peter; Marschallinger, Robert

    2014-05-01

    Halite hopper crystals are thought to develop by displacive growth in unconsolidated mud (Gornitz & Schreiber, 1984). The Alpine Haselgebirge, but also e.g. the salt deposits of the Rhine graben (mined at the beginning of the 20th century), comprise hopper crystals with shapes of cuboids, parallelepipeds and rhombohedrons (Görgey, 1912). Obviously, they deformed under oriented stress, which had been tried to reconstruct with respect to the sedimentary layering (Leitner et al., 2013). In the present work, deformed halite hopper crystals embedded in mudrock were automated reconstructed. Object based image analysis (OBIA) has been used successfully in remote sensing for 2D images before. The present study represents the first time that the method was used for reconstruction of three dimensional geological objects. First, manually a reference (gold standard) was created by redrawing contours of the halite crystals on each HRXCT scanning slice. Then, for OBIA, the computer program eCognition was used. For the automated reconstruction a rule set was developed. Thereby, the strength of OBIA was to recognize all objects similar to halite hopper crystals and in particular to eliminate cracks. In a second step, all the objects unsuitable for a structural deformation analysis were dismissed using a support vector machine (SVM) (clusters, polyhalite-coated crystals and spherical halites) The SVM simultaneously drastically reduced the number of halites. From 184 OBIA-objects 67 well shaped remained, which comes close to the number of pre-selected 52 objects. To assess the accuracy of the automated reconstruction, the result before and after SVM was compared to the reference, i.e. the gold standard. State-of the art per-scene statistics were extended to a per-object statistics. Görgey R (1912) Zur Kenntnis der Kalisalzlager von Wittelsheim im Ober-Elsaß. Tschermaks Mineral Petrogr Mitt 31:339-468 Gornitz VM, Schreiber BC (1981) Displacive halite hoppers from the dead sea

  6. 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…

  7. Recognition of Single and Overlay of Objects on a Conveyor Belt

    NASA Astrophysics Data System (ADS)

    Savicheva, S. V.

    2015-05-01

    Proposed a method for detection of flat objects when they overlap condition. The method is based on two separate recognition algorithms flat objects. The first algorithm is based on a binary image of the signature of the object plane. The second algorithm is based on the values of the discrete points in the curvature contour of a binary image. The results of experimental studies of algorithms and a method of recognition of individual superimposed flat objects.

  8. 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. PMID:23644160

  9. 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.

  10. 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…

  11. 3D multi-object segmentation of cardiac MSCT imaging by using a multi-agent approach.

    PubMed

    Fleureau, Julien; Garreau, Mireille; Boulmier, Dominique; Hernández, Alfredo

    2007-01-01

    We propose a new technique for general purpose, semi-interactive and multi-object segmentation in N-dimensional images, applied to the extraction of cardiac structures in MultiSlice Computed Tomography (MSCT) imaging. The proposed approach makes use of a multi-agent scheme combined with a supervised classification methodology allowing the introduction of a priori information and presenting fast computing times. The multi-agent system is organised around a communicating agent which manages a population of situated agents which segment the image through cooperative and competitive interactions. The proposed technique has been tested on several patient data sets. Some typical results are finally presented and discussed. PMID:18003382

  12. 3D Multi-Object Segmentation of Cardiac MSCT Imaging by using a Multi-Agent Approach

    PubMed Central

    Fleureau, Julien; Garreau, Mireille; Boulmier, Dominique; Hernandez, Alfredo

    2007-01-01

    We propose a new technique for general purpose, semi-interactive and multi-object segmentation in N-dimensional images, applied to the extraction of cardiac structures in MultiSlice Computed Tomography (MSCT) imaging. The proposed approach makes use of a multi-agent scheme combined with a supervised classification methodology allowing the introduction of a priori information and presenting fast computing times. The multi-agent system is organised around a communicating agent which manages a population of situated agents which segment the image through cooperative and competitive interactions. The proposed technique has been tested on several patient data sets. Some typical results are finally presented and discussed. PMID:18003382

  13. Model-based object recognition in range imagery

    NASA Astrophysics Data System (ADS)

    Armbruster, Walter

    2009-09-01

    The paper formulates the mathematical foundations of object discrimination and object re-identification in range image sequences using Bayesian decision theory. Object discrimination determines the unique model corresponding to each scene object, while object re-identification finds the unique object in the scene corresponding to a given model. In the first case object identities are independent; in the second case at most one object exists having a given identity. Efficient analytical and numerical techniques for updating and maximizing the posterior distributions are introduced. Experimental results indicate to what extent a single range image of an object can be used for re-identifying this object in arbitrary scenes. Applications including the protection of commercial vessels against piracy are discussed.

  14. Delaunay-Object-Dynamics: cell mechanics with a 3D kinetic and dynamic weighted Delaunay-triangulation.

    PubMed

    Meyer-Hermann, Michael

    2008-01-01

    Mathematical methods in Biology are of increasing relevance for understanding the control and the dynamics of biological systems with medical relevance. In particular, agent-based methods turn more and more important because of fast increasing computational power which makes even large systems accessible. An overview of different mathematical methods used in Theoretical Biology is provided and a novel agent-based method for cell mechanics based on Delaunay-triangulations and Voronoi-tessellations is explained in more detail: The Delaunay-Object-Dynamics method. It is claimed that the model combines physically realistic cell mechanics with a reasonable computational load. The power of the approach is illustrated with two examples, avascular tumor growth and genesis of lymphoid tissue in a cell-flow equilibrium. PMID:18023735

  15. How Does Using Object Names Influence Visual Recognition Memory?

    ERIC Educational Resources Information Center

    Richler, Jennifer J.; Palmeri, Thomas J.; Gauthier, Isabel

    2013-01-01

    Two recent lines of research suggest that explicitly naming objects at study influences subsequent memory for those objects at test. Lupyan (2008) suggested that naming "impairs" memory by a representational shift of stored representations of named objects toward the prototype (labeling effect). MacLeod, Gopie, Hourihan, Neary, and Ozubko (2010)…

  16. Symbolic Play Connects to Language through Visual Object Recognition

    ERIC Educational Resources Information Center

    Smith, Linda B.; Jones, Susan S.

    2011-01-01

    Object substitutions in play (e.g. using a box as a car) are strongly linked to language learning and their absence is a diagnostic marker of language delay. Classic accounts posit a symbolic function that underlies both words and object substitutions. Here we show that object substitutions depend on developmental changes in visual object…

  17. 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

  18. A novel window based method for approximating the Hausdorff in 3D range imagery.

    SciTech Connect

    Koch, Mark William

    2004-10-01

    Matching a set of 3D points to another set of 3D points is an important part of any 3D object recognition system. The Hausdorff distance is known for it robustness in the face of obscuration, clutter, and noise. We show how to approximate the 3D Hausdorff fraction with linear time complexity and quadratic space complexity. We empirically demonstrate that the approximation is very good when compared to actual Hausdorff distances.

  19. Developmental changes in visual object recognition between 18 and 24 months of age

    PubMed Central

    Pereira, Alfredo F.; Smith, Linda B.

    2010-01-01

    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 global shape information, color, textural and featural information, (2) the same rich and prototypical shapes but no color, texture or surface featural information, or (3) that presented only abstract and global representations of object shape in terms of geometric volumes. Significant developmental differences were observed only for the abstract shape representations in terms of geometric volumes, the kind of shape representation that has been hypothesized to underlie mature object recognition. Further, these differences were strongly linked in individual children to the number of object names in their productive vocabulary. Experiment 2 replicated these results and showed further that the less advanced children’s object recognition was based on the piecemeal use of individual features and parts, rather than overall shape. The results provide further evidence for significant and rapid developmental changes in object recognition during the same period children first learn object names. The implications of the results for theories of visual object recognition, the relation of object recognition to category learning, and underlying developmental processes are discussed. PMID:19120414

  20. Demonstration of a 3D vision algorithm for space applications

    NASA Technical Reports Server (NTRS)

    Defigueiredo, Rui J. P. (Editor)

    1987-01-01

    This paper reports an extension of the MIAG algorithm for recognition and motion parameter determination of general 3-D polyhedral objects based on model matching techniques and using movement invariants as features of object representation. Results of tests conducted on the algorithm under conditions simulating space conditions are presented.

  1. Representational dynamics of object recognition: Feedforward and feedback information flows.

    PubMed

    Goddard, Erin; Carlson, Thomas A; Dermody, Nadene; Woolgar, Alexandra

    2016-03-01

    Object perception involves a range of visual and cognitive processes, and is known to include both a feedfoward flow of information from early visual cortical areas to higher cortical areas, along with feedback from areas such as prefrontal cortex. Previous studies have found that low and high spatial frequency information regarding object identity may be processed over different timescales. Here we used the high temporal resolution of magnetoencephalography (MEG) combined with multivariate pattern analysis to measure information specifically related to object identity in peri-frontal and peri-occipital areas. Using stimuli closely matched in their low-level visual content, we found that activity in peri-occipital cortex could be used to decode object identity from ~80ms post stimulus onset, and activity in peri-frontal cortex could also be used to decode object identity from a later time (~265ms post stimulus onset). Low spatial frequency information related to object identity was present in the MEG signal at an earlier time than high spatial frequency information for peri-occipital cortex, but not for peri-frontal cortex. We additionally used Granger causality analysis to compare feedforward and feedback influences on representational content, and found evidence of both an early feedfoward flow and later feedback flow of information related to object identity. We discuss our findings in relation to existing theories of object processing and propose how the methods we use here could be used to address further questions of the neural substrates underlying object perception. PMID:26806290

  2. An object-oriented environment for computer vision and pattern recognition

    SciTech Connect

    Hernandez, J.E.

    1992-12-01

    Vision is a flexible and extensible object-oriented programming environment for prototyping solutions to problems requiring computer vision and pattern recognition techniques. Vision integrates signal/image processing, statistical pattern recognition, neural networks, low and mid level computer vision, and graphics into a cohesive framework useful for a wide variety of applications at Lawrence Livermore National Laboratory.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26246157

  4. Object Recognition with Severe Spatial Deficits in Williams Syndrome: Sparing and Breakdown

    ERIC Educational Resources Information Center

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

    2006-01-01

    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…

  5. Fuzzy set methods for object recognition in space applications

    NASA Technical Reports Server (NTRS)

    Keller, James M.

    1991-01-01

    Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

  6. Software for optical recognition of micro- and nano-objects in solids and colloidal solutions

    NASA Astrophysics Data System (ADS)

    Val', O.; Diachenko, L.; Minov, E.; Ostapov, S.; Fochuk, P.; Khalavka, Yu.; Kopach, O.

    2015-11-01

    This paper deals with the development of algorithms and software for optical recognition of growing defects in the semiconductor crystals and metal nanoparticles in colloidal solutions. Input information is a set of photographs from a microscope, as well as a short video-file with nanoparticle's tracks. We used the wavelet technology to filtering and image transformations. As a result of recognition the 3D image is formed with the point, linear and planar growing defects. Defects are sorted by size; different statistical characteristics are computed such as the defect's distribution in layers and in the whole crystal. The system supports arbitrary rotations of the "crystal"; "cutting" by different planes and so on. The software allows you to track the movement of nanoparticles in colloidal solutions; to determine the local temperature and density of the solution. We proposed a new method for quantitative estimation of recognition quality. This method based on the "virtual crystal" model, which has predetermined parameters of the defect subsystem. The software generates a set of photographs, which used as the input information of recognition system. Comparing the statistical parameters of the input data with the recognition results, we can estimate the quality of recognition systems from different manufacturers.

  7. 3-D visualisation of palaeoseismic trench stratigraphy and trench logging using terrestrial remote sensing and GPR - combining techniques towards an objective multiparametric interpretation

    NASA Astrophysics Data System (ADS)

    Schneiderwind, S.; Mason, J.; Wiatr, T.; Papanikolaou, I.; Reicherter, K.

    2015-09-01

    Two normal faults on the Island of Crete and mainland Greece were studied to create and test an innovative workflow to make palaeoseismic trench logging more objective, and visualise the sedimentary architecture within the trench wall in 3-D. This is achieved by combining classical palaeoseismic trenching techniques with multispectral approaches. A conventional trench log was firstly compared to results of iso cluster analysis of a true colour photomosaic representing the spectrum of visible light. Passive data collection disadvantages (e.g. illumination) were addressed by complementing the dataset with active near-infrared backscatter signal image from t-LiDAR measurements. The multispectral analysis shows that distinct layers can be identified and it compares well with the conventional trench log. According to this, a distinction of adjacent stratigraphic units was enabled by their particular multispectral composition signature. Based on the trench log, a 3-D-interpretation of GPR data collected on the vertical trench wall was then possible. This is highly beneficial for measuring representative layer thicknesses, displacements and geometries at depth within the trench wall. Thus, misinterpretation due to cutting effects is minimised. Sedimentary feature geometries related to earthquake magnitude can be used to improve the accuracy of seismic hazard assessments. Therefore, this manuscript combines multiparametric approaches and shows: (i) how a 3-D visualisation of palaeoseismic trench stratigraphy and logging can be accomplished by combining t-LiDAR and GRP techniques, and (ii) how a multispectral digital analysis can offer additional advantages and a higher objectivity in the interpretation of palaeoseismic and stratigraphic information. The multispectral datasets are stored allowing unbiased input for future (re-)investigations.

  8. Object recognition through turbulence with a modified plenoptic camera

    NASA Astrophysics Data System (ADS)

    Wu, Chensheng; Ko, Jonathan; Davis, Christopher

    2015-03-01

    Atmospheric turbulence adds accumulated distortion to images obtained by cameras and surveillance systems. When the turbulence grows stronger or when the object is further away from the observer, increasing the recording device resolution helps little to improve the quality of the image. Many sophisticated methods to correct the distorted images have been invented, such as using a known feature on or near the target object to perform a deconvolution process, or use of adaptive optics. However, most of the methods depend heavily on the object's location, and optical ray propagation through the turbulence is not directly considered. Alternatively, selecting a lucky image over many frames provides a feasible solution, but at the cost of time. In our work, we propose an innovative approach to improving image quality through turbulence by making use of a modified plenoptic camera. This type of camera adds a micro-lens array to a traditional high-resolution camera to form a semi-camera array that records duplicate copies of the object as well as "superimposed" turbulence at slightly different angles. By performing several steps of image reconstruction, turbulence effects will be suppressed to reveal more details of the object independently (without finding references near the object). Meanwhile, the redundant information obtained by the plenoptic camera raises the possibility of performing lucky image algorithmic analysis with fewer frames, which is more efficient. In our work, the details of our modified plenoptic cameras and image processing algorithms will be introduced. The proposed method can be applied to coherently illuminated object as well as incoherently illuminated objects. Our result shows that the turbulence effect can be effectively suppressed by the plenoptic camera in the hardware layer and a reconstructed "lucky image" can help the viewer identify the object even when a "lucky image" by ordinary cameras is not achievable.

  9. 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. PMID:21038986

  10. Combined robotic-aided gait training and 3D gait analysis provide objective treatment and assessment of gait in children and adolescents with Acquired Hemiplegia.

    PubMed

    Molteni, Erika; Beretta, Elena; Altomonte, Daniele; Formica, Francesca; Strazzer, Sandra

    2015-08-01

    To evaluate the feasibility of a fully objective rehabilitative and assessment process of the gait abilities in children suffering from Acquired Hemiplegia (AH), we studied the combined employment of robotic-aided gait training (RAGT) and 3D-Gait Analysis (GA). A group of 12 patients with AH underwent 20 sessions of RAGT in addition to traditional manual physical therapy (PT). All the patients were evaluated before and after the training by using the Gross Motor Function Measures (GMFM), the Functional Assessment Questionnaire (FAQ), and the 6 Minutes Walk Test. They also received GA before and after RAGT+PT. Finally, results were compared with those obtained from a control group of 3 AH children who underwent PT only. After the training, the GMFM and FAQ showed significant improvement in patients receiving RAGT+PT. GA highlighted significant improvement in stance symmetry and step length of the affected limb. Moreover, pelvic tilt increased, and hip kinematics on the sagittal plane revealed statistically significant increase in the range of motion during the hip flex-extension. Our data suggest that the combined program RAGT+PT induces improvements in functional activities and gait pattern in children with AH, and it demonstrates that the combined employment of RAGT and 3D-GA ensures a fully objective rehabilitative program. PMID:26737310

  11. Hip2Norm: an object-oriented cross-platform program for 3D analysis of hip joint morphology using 2D pelvic radiographs.

    PubMed

    Zheng, G; Tannast, M; Anderegg, C; Siebenrock, K A; Langlotz, F

    2007-07-01

    We developed an object-oriented cross-platform program to perform three-dimensional (3D) analysis of hip joint morphology using two-dimensional (2D) anteroposterior (AP) pelvic radiographs. Landmarks extracted from 2D AP pelvic radiographs and optionally an additional lateral pelvic X-ray were combined with a cone beam projection model to reconstruct 3D hip joints. Since individual pelvic orientation can vary considerably, a method for standardizing pelvic orientation was implemented to determine the absolute tilt/rotation. The evaluation of anatomically morphologic differences was achieved by reconstructing the projected acetabular rim and the measured hip parameters as if obtained in a standardized neutral orientation. The program had been successfully used to interactively objectify acetabular version in hips with femoro-acetabular impingement or developmental dysplasia. Hip(2)Norm is written in object-oriented programming language C++ using cross-platform software Qt (TrollTech, Oslo, Norway) for graphical user interface (GUI) and is transportable to any platform. PMID:17499878

  12. Storing a 3d City Model, its Levels of Detail and the Correspondences Between Objects as a 4d Combinatorial Map

    NASA Astrophysics Data System (ADS)

    Arroyo Ohori, K.; Ledoux, H.; Stoter, J.

    2015-10-01

    3D city models of the same region at multiple LODs are encumbered by the lack of links between corresponding objects across LODs. In practice, this causes inconsistency during updates and maintenance problems. A radical solution to this problem is to model the LOD of a model as a dimension in the geometric sense, such that a set of connected polyhedra at a series of LODs is modelled as a single polychoron—the 4D analogue of a polyhedron. This approach is generally used only conceptually and then discarded at the implementation stage, losing many of its potential advantages in the process. This paper therefore shows that this approach can be instead directly realised using 4D combinatorial maps, making it possible to store all topological relationships between objects.

  13. The Neural Basis of Nonvisual Object Recognition Memory in the Rat

    PubMed Central

    Albasser, Mathieu M.; Olarte-Sánchez, Cristian M.; Amin, Eman; Horne, Murray R.; Newton, Michael J.; Warburton, E. Clea; Aggleton, John P.

    2012-01-01

    Research into the neural basis of recognition memory has traditionally focused on the remembrance of visual stimuli. The present study examined the neural basis of object recognition memory in the dark, with a view to determining the extent to which it shares common pathways with visual-based object recognition. Experiment 1 assessed the expression of the immediate-early gene c-fos in rats that discriminated novel from familiar objects in the dark (Group Novel). Comparisons made with a control group that explored only familiar objects (Group Familiar) showed that Group Novel had higher c-fos activity in the rostral perirhinal cortex and the lateral entorhinal cortex. Outside the temporal region, Group Novel showed relatively increased c-fos activity in the anterior medial thalamic nucleus and the anterior cingulate cortex. Both the hippocampal CA fields and the granular retrosplenial cortex showed borderline increases in c-fos activity with object novelty. The hippocampal findings prompted Experiment 2. Here, rats with hippocampal lesions were tested in the dark for object recognition memory at different retention delays. Across two replications, no evidence was found that hippocampal lesions impair nonvisual object recognition. The results indicate that in the dark, as in the light, interrelated parahippocampal sites are activated when rats explore novel stimuli. These findings reveal a network of linked c-fos activations that share superficial features with those associated with visual recognition but differ in the fine details; for example, in the locus of the perirhinal cortex activation. While there may also be a relative increase in c-fos activation in the extended-hippocampal system to object recognition in the dark, there was no evidence that this recognition memory problem required an intact hippocampus. PMID:23244291

  14. Do Simultaneously Viewed Objects Influence Scene Recognition Individually or as Groups? Two Perceptual Studies

    PubMed Central

    Gagne, Christopher R.; MacEvoy, Sean P.

    2014-01-01

    The ability to quickly categorize visual scenes is critical to daily life, allowing us to identify our whereabouts and to navigate from one place to another. Rapid scene categorization relies heavily on the kinds of objects scenes contain; for instance, studies have shown that recognition is less accurate for scenes to which incongruent objects have been added, an effect usually interpreted as evidence of objects' general capacity to activate semantic networks for scene categories they are statistically associated with. Essentially all real-world scenes contain multiple objects, however, and it is unclear whether scene recognition draws on the scene associations of individual objects or of object groups. To test the hypothesis that scene recognition is steered, at least in part, by associations between object groups and scene categories, we asked observers to categorize briefly-viewed scenes appearing with object pairs that were semantically consistent or inconsistent with the scenes. In line with previous results, scenes were less accurately recognized when viewed with inconsistent versus consistent pairs. To understand whether this reflected individual or group-level object associations, we compared the impact of pairs composed of mutually related versus unrelated objects; i.e., pairs, which, as groups, had clear associations to particular scene categories versus those that did not. Although related and unrelated object pairs equally reduced scene recognition accuracy, unrelated pairs were consistently less capable of drawing erroneous scene judgments towards scene categories associated with their individual objects. This suggests that scene judgments were influenced by the scene associations of object groups, beyond the influence of individual objects. More generally, the fact that unrelated objects were as capable of degrading categorization accuracy as related objects, while less capable of generating specific alternative judgments, indicates that the process

  15. Dissociating the Effects of Angular Disparity and Image Similarity in Mental Rotation and Object Recognition

    ERIC Educational Resources Information Center

    Cheung, Olivia S.; Hayward, William G.; Gauthier, Isabel

    2009-01-01

    Performance is often impaired linearly with increasing angular disparity between two objects in tasks that measure mental rotation or object recognition. But increased angular disparity is often accompanied by changes in the similarity between views of an object, confounding the impact of the two factors in these tasks. We examined separately the…

  16. 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…

  17. Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images

    PubMed Central

    Kim, Sungho; Shim, Min-Sheob

    2015-01-01

    This paper presents the novel paradigm of a global localization method motivated by human visual systems (HVSs). HVSs actively use the information of the object recognition results for self-position localization and for viewing direction. The proposed localization paradigm consisted of three parts: panoramic image acquisition, multiple object recognition, and grid-based localization. Multiple object recognition information from panoramic images is utilized in the localization part. High-level object information was useful not only for global localization, but also for robot-object interactions. The metric global localization (position, viewing direction) was conducted based on the bearing information of recognized objects from just one panoramic image. The feasibility of the novel localization paradigm was validated experimentally. PMID:26457323

  18. Object recognition based on spatial active basis template

    NASA Astrophysics Data System (ADS)

    Peng, Shaowu; Xu, Jingcheng

    2011-11-01

    This article presents a method for the object classification that combines a generative template and a discriminative classifier. The method is a variant of the support vector machine (SVM), which uses Multiple Kernel Learning (MKL). The features are extracted from a generative template so called Active Basis template. Before using them for object classification, we construct a visual vocabulary by clustering a set of training features according to their orientations. To keep the spatial information, a "spatial pyramid" is used. The strength of this approach is that it combines the rich information encoded in the generative template, the Active Basis, with the discriminative power of the SVM algorithm. We show promising results of experiments for images from the LHI dataset.

  19. Graph - Based High Resolution Satellite Image Segmentation for Object Recognition

    NASA Astrophysics Data System (ADS)

    Ravali, K.; Kumar, M. V. Ravi; Venugopala Rao, K.

    2014-11-01

    Object based image processing and analysis is challenging research in very high resolution satellite utilisation. Commonly ei ther pixel based classification or visual interpretation is used to recognize and delineate land cover categories. The pixel based classification techniques use rich spectral content of satellite images and fail to utilise spatial relations. To overcome th is drawback, traditional time consuming visual interpretation methods are being used operational ly for preparation of thematic maps. This paper addresses computational vision principles to object level image segmentation. In this study, computer vision algorithms are developed to define the boundary between two object regions and segmentation by representing image as graph. Image is represented as a graph G (V, E), where nodes belong to pixels and, edges (E) connect nodes belonging to neighbouring pixels. The transformed Mahalanobis distance has been used to define a weight function for partition of graph into components such that each component represents the region of land category. This implies that edges between two vertices in the same component have relatively low weights and edges between vertices in different components should have higher weights. The derived segments are categorised to different land cover using supervised classification. The paper presents the experimental results on real world multi-spectral remote sensing images of different landscapes such as Urban, agriculture and mixed land cover. Graph construction done in C program and list the run time for both graph construction and segmentation calculation on dual core Intel i7 system with 16 GB RAM, running 64bit window 7.

  20. The impact of interactive manipulation on the recognition of objects

    NASA Astrophysics Data System (ADS)

    Meijer, Frank; van den Broek, Egon L.; Schouten, Theo

    2008-02-01

    A new application for VR has emerged: product development, in which several stakeholders (from engineers to end users) use the same VR for development and communicate purposes. Various characteristics among these stakeholders vary considerably, which imposes potential constraints to the VR. The current paper discusses the influence of three types of exploration of objects (i.e., none, passive, active) on one of these characteristics: the ability to form mental representations or visuo-spatial ability (VSA). Through an experiment we found that all users benefit from exploring objects. Moreover, people with low VSA (e.g., end users) benefit from an interactive exploration of objects opposed to people with a medium or high VSA (e.g. engineers), who are not sensitive for the type of exploration. Hence, for VR environments in which multiple stakeholders participate (e.g. for product development), differences among their cognitive abilities (e.g., VSA) have to be taken into account to enable an efficient usage of VR.

  1. 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

  2. Active and interactive floating image display using holographic 3D images

    NASA Astrophysics Data System (ADS)

    Morii, Tsutomu; Sakamoto, Kunio

    2006-08-01

    We developed a prototype tabletop holographic display system. This system consists of the object recognition system and the spatial imaging system. In this paper, we describe the recognition system using an RFID tag and the 3D display system using a holographic technology. A 3D display system is useful technology for virtual reality, mixed reality and augmented reality. We have researched spatial imaging and interaction system. We have ever proposed 3D displays using the slit as a parallax barrier, the lenticular screen and the holographic optical elements(HOEs) for displaying active image 1,2,3. The purpose of this paper is to propose the interactive system using these 3D imaging technologies. In this paper, the authors describe the interactive tabletop 3D display system. The observer can view virtual images when the user puts the special object on the display table. The key technologies of this system are the object recognition system and the spatial imaging display.

  3. Multi-class remote sensing object recognition based on discriminative sparse representation.

    PubMed

    Wang, Xin; Shen, Siqiu; Ning, Chen; Huang, Fengchen; Gao, Hongmin

    2016-02-20

    The automatic recognition of multi-class objects with various backgrounds is a big challenge in the field of remote sensing (RS) image analysis. In this paper, we propose a novel recognition framework for multi-class RS objects based on the discriminative sparse representation. In this framework, the recognition problem is implemented in two stages. In the first, or discriminative dictionary learning stage, considering the characterization of remote sensing objects, the scale-invariant feature transform descriptor is first combined with an improved bag-of-words model for multi-class objects feature extraction and representation. Then, information about each class of training samples is fused into the dictionary learning process; by using the K-singular value decomposition algorithm, a discriminative dictionary can be learned for sparse coding. In the second, or recognition, stage, to improve the computational efficiency, the phase spectrum of a quaternion Fourier transform model is applied to the test image to predict a small set of object candidate locations. Then, a multi-scale sliding window mechanism is utilized to scan the image over those candidate locations to obtain the object candidates (or objects of interest). Subsequently, the sparse coding coefficients of these candidates under the discriminative dictionary are mapped to the discriminative vectors that have a good ability to distinguish different classes of objects. Finally, multi-class object recognition can be accomplished by analyzing these vectors. The experimental results show that the proposed work outperforms a number of state-of-the-art methods for multi-class remote sensing object recognition. PMID:26906591

  4. Stochastic Process Underlying Emergent Recognition of Visual Objects Hidden in Degraded Images

    PubMed Central

    Murata, Tsutomu; Hamada, Takashi; Shimokawa, Tetsuya; Tanifuji, Manabu; Yanagida, Toshio

    2014-01-01

    When a degraded two-tone image such as a “Mooney” image is seen for the first time, it is unrecognizable in the initial seconds. The recognition of such an image is facilitated by giving prior information on the object, which is known as top-down facilitation and has been intensively studied. Even in the absence of any prior information, however, we experience sudden perception of the emergence of a salient object after continued observation of the image, whose processes remain poorly understood. This emergent recognition is characterized by a comparatively long reaction time ranging from seconds to tens of seconds. In this study, to explore this time-consuming process of emergent recognition, we investigated the properties of the reaction times for recognition of degraded images of various objects. The results show that the time-consuming component of the reaction times follows a specific exponential function related to levels of image degradation and subject's capability. Because generally an exponential time is required for multiple stochastic events to co-occur, we constructed a descriptive mathematical model inspired by the neurophysiological idea of combination coding of visual objects. Our model assumed that the coincidence of stochastic events complement the information loss of a degraded image leading to the recognition of its hidden object, which could successfully explain the experimental results. Furthermore, to see whether the present results are specific to the task of emergent recognition, we also conducted a comparison experiment with the task of perceptual decision making of degraded images, which is well known to be modeled by the stochastic diffusion process. The results indicate that the exponential dependence on the level of image degradation is specific to emergent recognition. The present study suggests that emergent recognition is caused by the underlying stochastic process which is based on the coincidence of multiple stochastic events

  5. 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

  6. Object recognition impairment and rescue by a dopamine D2 antagonist in hyperdopaminergic mice.

    PubMed

    França, Arthur S C; Muratori, Larissa; Nascimento, George Carlos; Pereira, Catia Mendes; Ribeiro, Sidarta; Lobão-Soares, Bruno

    2016-07-15

    Genetically-modified mice without the dopamine transporter (DAT) are hyperdopaminergic, and serve as models for studies of addiction, mania and hyperactive disorders. Here we investigated the capacity for object recognition in mildly hyperdopaminergic mice heterozygous for DAT (DAT +/-), with synaptic dopaminergic levels situated between those shown by DAT -/- homozygous and wild-type (WT) mice. We used a classical dopamine D2 antagonist, haloperidol, to modulate the levels of dopaminergic transmission in a dose-dependent manner, before or after exploring novel objects. In comparison with WT mice, DAT +/- mice showed a deficit in object recognition upon subsequent testing 24h later. This deficit was compensated by a single 0.05mg/kg haloperidol injection 30min before training. In all mice, a 0.3mg/kg haloperidol injected immediately after training impaired object recognition. The results indicate that a mild enhancement of dopaminergic levels can be detrimental to object recognition, and that this deficit can be rescued by a low dose of a D2 dopamine receptor antagonist. This suggests that novel object recognition is optimal at intermediate levels of D2 receptor activity. PMID:27059337

  7. Expertise modulates the neural basis of context dependent recognition of objects and their relations.

    PubMed

    Bilalić, Merim; Turella, Luca; Campitelli, Guillermo; Erb, Michael; Grodd, Wolfgang

    2012-11-01

    Recognition of objects and their relations is necessary for orienting in real life. We examined cognitive processes related to recognition of objects, their relations, and the patterns they form by using the game of chess. Chess enables us to compare experts with novices and thus gain insight in the nature of development of recognition skills. Eye movement recordings showed that experts were generally faster than novices on a task that required enumeration of relations between chess objects because their extensive knowledge enabled them to immediately focus on the objects of interest. The advantage was less pronounced on random positions wher