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.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Three-dimensional object recognitions from two-dimensional images using wavelet transforms and neural networks

NASA Astrophysics Data System (ADS)

Deschenes, Sylvain; Sheng, Yunlong; Chevrette, Paul C.

1998-03-01

3D object classification from 2D IR images is shown. The wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively int he wavelet transform. The invariant Fourier descriptor is used to describe the contour curves. Invariance under out-of-plane rotation is achieved by the feature space trajectory neural network working as a classifier.

Strongest Earthquake-Prone Areas in Kamchatka

NASA Astrophysics Data System (ADS)

Dzeboev, B. A.; Agayan, S. M.; Zharkikh, Yu. I.; Krasnoperov, R. I.; Barykina, Yu. V.

2018-03-01

The paper continues the series of our works on recognizing the areas prone to the strongest, strong, and significant earthquakes with the use of the Formalized Clustering And Zoning (FCAZ) intellectual clustering system. We recognized the zones prone to the probable emergence of epicenters of the strongest ( M ≥ 74/3) earthquakes on the Pacific Coast of Kamchatka. The FCAZ-zones are compared to the zones that were recognized in 1984 by the classical recognition method for Earthquake-Prone Areas (EPA) by transferring the criteria of high seismicity from the Andes mountain belt to the territory of Kamchatka. The FCAZ recognition was carried out with two-dimensional and three-dimensional objects of recognition.

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation, final phase

NASA Technical Reports Server (NTRS)

Mielke, Roland; Dcunha, Ivan; Alvertos, Nicolas

1994-01-01

In the final phase of the proposed research a complete top to down three dimensional object recognition scheme has been proposed. The various three dimensional objects included spheres, cones, cylinders, ellipsoids, paraboloids, and hyperboloids. Utilizing a newly developed blob determination technique, a given range scene with several non-cluttered quadric surfaces is segmented. Next, using the earlier (phase 1) developed alignment scheme, each of the segmented objects are then aligned in a desired coordinate system. For each of the quadric surfaces based upon their intersections with certain pre-determined planes, a set of distinct features (curves) are obtained. A database with entities such as the equations of the planes and angular bounds of these planes has been created for each of the quadric surfaces. Real range data of spheres, cones, cylinders, and parallelpipeds have been utilized for the recognition process. The developed algorithm gave excellent results for the real data as well as for several sets of simulated range data.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

PubMed

Vurro, Milena; Ling, Yazhu; Hurlbert, Anya C

2013-06-28

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

Virtual Environment for Surgical Room of the Future.

DTIC Science & Technology

1995-10-01

Design; 1. wire frame Dynamic Interaction 2. surface B. Acoustic Three-Dimensional Modeling; 3. solid based on radiosity modeling B. Dynamic...infection control of people and E. Rendering and Shadowing equipment 1. ray tracing D. Fluid Flow 2. radiosity F. Animation OBJECT RECOGNITION COMMUNICATION

On-line analysis of algae in water by discrete three-dimensional fluorescence spectroscopy.

PubMed

Zhao, Nanjing; Zhang, Xiaoling; Yin, Gaofang; Yang, Ruifang; Hu, Li; Chen, Shuang; Liu, Jianguo; Liu, Wenqing

2018-03-19

In view of the problem of the on-line measurement of algae classification, a method of algae classification and concentration determination based on the discrete three-dimensional fluorescence spectra was studied in this work. The discrete three-dimensional fluorescence spectra of twelve common species of algae belonging to five categories were analyzed, the discrete three-dimensional standard spectra of five categories were built, and the recognition, classification and concentration prediction of algae categories were realized by the discrete three-dimensional fluorescence spectra coupled with non-negative weighted least squares linear regression analysis. The results show that similarities between discrete three-dimensional standard spectra of different categories were reduced and the accuracies of recognition, classification and concentration prediction of the algae categories were significantly improved. By comparing with that of the chlorophyll a fluorescence excitation spectra method, the recognition accuracy rate in pure samples by discrete three-dimensional fluorescence spectra is improved 1.38%, and the recovery rate and classification accuracy in pure diatom samples 34.1% and 46.8%, respectively; the recognition accuracy rate of mixed samples by discrete-three dimensional fluorescence spectra is enhanced by 26.1%, the recovery rate of mixed samples with Chlorophyta 37.8%, and the classification accuracy of mixed samples with diatoms 54.6%.

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.

Strategies for the Interpretive Integration of Ground and Aerial Views in UGV Operations

DTIC Science & Technology

2006-11-01

conjoinment of the psychological processes and effects of perception, object recognition (i.e. Biederman & Gerhardstein, 1993), navigation (Wickens...rather simple geon structural descriptions (GSD, see Biederman & 4 Gerhardstein, 1993). A geon is a basic three dimensional solid shape, such as a...large and reliable sex difference. Behavioral Brain Research, 93, 185-190. Biederman , I., & Gerhardstein, C. (1993). Recognizing depth- rotated objects

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 directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

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

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.

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

PubMed

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

2018-05-15

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

Stereo vision with distance and gradient recognition

NASA Astrophysics Data System (ADS)

Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

2007-12-01

Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

Shape Recognition Inputs to Figure-Ground Organization in Three-Dimensional Displays.

ERIC Educational Resources Information Center

Peterson, Mary A.; Gibson, Bradley S.

1993-01-01

Three experiments with 29 college students and 8 members of a university community demonstrate that shape recognition processes influence perceived figure-ground relationships in 3-dimensional displays when the edge between 2 potential figural regions is both a luminance contrast edge and a disparity edge. Implications for shape recognition and…

Representation of 3-Dimenstional Objects by the Rat Perirhinal Cortex

PubMed Central

Burke, S.N.; Maurer, A.P.; Hartzell, A.L.; Nematollahi, S.; Uprety, A.; Wallace, J.L.; Barnes, C.A.

2012-01-01

The perirhinal cortex (PRC) is known to play an important role in object recognition. Little is known, however, regarding the activity of PRC neurons during the presentation of stimuli that are commonly used for recognition memory tasks in rodents, that is, 3-dimensional objects. Rats in the present study were exposed to 3-dimensional objects while they traversed a circular track for food reward. Under some behavioral conditions the track contained novel objects, familiar objects, or no objects. Approximately 38% of PRC neurons demonstrated ‘object fields’ (a selective increase in firing at the location of one or more objects). Although the rats spent more time exploring the objects when they were novel compared to familiar, indicating successful recognition memory, the proportion of object fields and the firing rates of PRC neurons were not affected by the rats’ previous experience with the objects. Together these data indicate that the activity of PRC cells is powerfully affected by the presence of objects while animals navigate through an environment, but under these conditions, the firing patterns are not altered by the relative novelty of objects during successful object recognition. PMID:22987680

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Case study of 3D fingerprints applications

PubMed Central

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition. PMID:28399141

Case study of 3D fingerprints applications.

PubMed

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition.

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 noise.

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

PubMed Central

2017-01-01

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

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Recognition of aspect-dependent three-dimensional objects by an echolocating Atlantic bottlenose dolphin.

PubMed

Helweg, D A; Roitblat, H L; Nachtigall, P E; Hautus, M J

1996-01-01

We examined the ability of a bottlenose dolphin (Tursiops truncatus) to recognize aspect-dependent objects using echolocation. An aspect-dependent object such as a cube produces acoustically different echoes at different angles relative to the echolocation signal. The dolphin recognized the objects even though the objects were free to rotate and sway. A linear discriminant analysis and nearest centroid classifier could classify the objects using average amplitude, center frequency, and bandwidth of object echoes. The results show that dolphins can use varying acoustic properties to recognize constant objects and suggest that aspect-independent representations may be formed by combining information gleaned from multiple echoes.

Continuous recognition of spatial and nonspatial stimuli in hippocampal-lesioned rats.

PubMed

Jackson-Smith, P; Kesner, R P; Chiba, A A

1993-03-01

The present experiments compared the performance of hippocampal-lesioned rats to control rats on a spatial continuous recognition task and an analogous nonspatial task with similar processing demands. Daily sessions for Experiment 1 involved sequential presentation of individual arms on a 12-arm radial maze. Each arm contained a Froot Loop reinforcement the first time it was presented, and latency to traverse the arm was measured. A subset of the arms were repeated, but did not contain reinforcement. Repeated arms were presented with lags ranging from 0 to 6 (0 to 6 different arm presentations occurred between the first and the repeated presentation). Difference scores were computed by subtracting the latency on first presentations from the latency on repeated presentations, and these scores were high in all rats prior to surgery, with a decreasing function across lag. There were no differences in performance following cortical control or sham surgery. However, there was a total deficit in performance following large electrolytic lesions of the hippocampus. The second experiment employed the same continuous recognition memory procedure, but used three-dimensional visual objects (toys, junk items, etc., in various shapes, sizes, and textures) as stimuli on a flat runway. As in Experiment 1, the stimuli were presented successively and latency to run to and move the object was measured. Objects were repeated with lags ranging from 0 to 4. Performance on this task following surgery did not differ from performance prior to surgery for either the control group or the hippocampal lesion group. These results provide support for Kesner's attribute model of hippocampal function in that the hippocampus is assumed to mediate data-based memory for spatial locations, but not three-dimensional visual objects.

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

A study of perceptual analysis in a high-level autistic subject with exceptional graphic abilities.

PubMed

Mottron, L; Belleville, S

1993-11-01

We report here the case study of a patient (E.C.) with an Asperger syndrome, or autism with quasinormal intelligence, who shows an outstanding ability for three-dimensional drawing of inanimate objects (savant syndrome). An assessment of the subsystems proposed in recent models of object recognition evidenced intact perceptual analysis and identification. The initial (or primal sketch), viewer-centered (or 2-1/2-D), or object-centered (3-D) representations and the recognition and name levels were functional. In contrast, E.C.'s pattern of performance in three different types of tasks converge to suggest an anomaly in the hierarchical organization of the local and global parts of a figure: a local interference effect in incongruent hierarchical visual stimuli, a deficit in relating local parts to global form information in impossible figures, and an absence of feature-grouping in graphic recall. The results are discussed in relation to normal visual perception and to current accounts of the savant syndrome in autism.

Cortical dynamics of three-dimensional figure-ground perception of two-dimensional pictures.

PubMed

Grossberg, S

1997-07-01

This article develops the FACADE theory of 3-dimensional (3-D) vision and figure-ground separation to explain data concerning how 2-dimensional pictures give rise to 3-D percepts of occluding and occluded objects. The model describes how geometrical and contrastive properties of a picture can either cooperate or compete when forming the boundaries and surface representation that subserve conscious percepts. Spatially long-range cooperation and spatially short-range competition work together to separate the boundaries of occluding figures from their occluded neighbors. This boundary ownership process is sensitive to image T junctions at which occluded figures contact occluding figures. These boundaries control the filling-in of color within multiple depth-sensitive surface representations. Feedback between surface and boundary representations strengthens consistent boundaries while inhibiting inconsistent ones. Both the boundary and the surface representations of occluded objects may be amodally completed, while the surface representations of unoccluded objects become visible through modal completion. Functional roles for conscious modal and amodal representations in object recognition, spatial attention, and reaching behaviors are discussed. Model interactions are interpreted in terms of visual, temporal, and parietal cortices.

OPTICAL INFORMATION PROCESSING: Synthesis of an object recognition system based on the profile of the envelope of a laser pulse in pulsed lidars

NASA Astrophysics Data System (ADS)

Buryi, E. V.

1998-05-01

The main problems in the synthesis of an object recognition system, based on the principles of operation of neuron networks, are considered. Advantages are demonstrated of a hierarchical structure of the recognition algorithm. The use of reading of the amplitude spectrum of signals as information tags is justified and a method is developed for determination of the dimensionality of the tag space. Methods are suggested for ensuring the stability of object recognition in the optical range. It is concluded that it should be possible to recognise perspectives of complex objects.

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation

NASA Technical Reports Server (NTRS)

Alvertos, Nicolas; Dcunha, Ivan

1993-01-01

The problem of recognizing and positioning of objects in three-dimensional space is important for robotics and navigation applications. In recent years, digital range data, also referred to as range images or depth maps, have been available for the analysis of three-dimensional objects owing to the development of several active range finding techniques. The distinct advantage of range images is the explicitness of the surface information available. Many industrial and navigational robotics tasks will be more easily accomplished if such explicit information can be efficiently interpreted. In this research, a new technique based on analytic geometry for the recognition and description of three-dimensional quadric surfaces from range images is presented. Beginning with the explicit representation of quadrics, a set of ten coefficients are determined for various three-dimensional surfaces. For each quadric surface, a unique set of two-dimensional curves which serve as a feature set is obtained from the various angles at which the object is intersected with a plane. Based on a discriminant method, each of the curves is classified as a parabola, circle, ellipse, hyperbola, or a line. Each quadric surface is shown to be uniquely characterized by a set of these two-dimensional curves, thus allowing discrimination from the others. Before the recognition process can be implemented, the range data have to undergo a set of pre-processing operations, thereby making it more presentable to classification algorithms. One such pre-processing step is to study the effect of median filtering on raw range images. Utilizing a variety of surface curvature techniques, reliable sets of image data that approximate the shape of a quadric surface are determined. Since the initial orientation of the surfaces is unknown, a new technique is developed wherein all the rotation parameters are determined and subsequently eliminated. This approach enables us to position the quadric surfaces in a desired coordinate system. Experiments were conducted on raw range images of spheres, cylinders, and cones. Experiments were also performed on simulated data for surfaces such as hyperboloids of one and two sheets, elliptical and hyperbolic paraboloids, elliptical and hyperbolic cylinders, ellipsoids and the quadric cones. Both the real and simulated data yielded excellent results. Our approach is found to be more accurate and computationally inexpensive as compared to traditional approaches, such as the three-dimensional discriminant approach which involves evaluation of the rank of a matrix. Finally, we have proposed one other new approach, which involves the formulation of a mapping between the explicit and implicit forms of representing quadric surfaces. This approach, when fully realized, will yield a three-dimensional discriminant, which will recognize quadric surfaces based upon their component surfaces patches. This approach is faster than prior approaches and at the same time is invariant to pose and orientation of the surfaces in three-dimensional space.

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation

NASA Astrophysics Data System (ADS)

Alvertos, Nicolas; Dcunha, Ivan

1993-03-01

The problem of recognizing and positioning of objects in three-dimensional space is important for robotics and navigation applications. In recent years, digital range data, also referred to as range images or depth maps, have been available for the analysis of three-dimensional objects owing to the development of several active range finding techniques. The distinct advantage of range images is the explicitness of the surface information available. Many industrial and navigational robotics tasks will be more easily accomplished if such explicit information can be efficiently interpreted. In this research, a new technique based on analytic geometry for the recognition and description of three-dimensional quadric surfaces from range images is presented. Beginning with the explicit representation of quadrics, a set of ten coefficients are determined for various three-dimensional surfaces. For each quadric surface, a unique set of two-dimensional curves which serve as a feature set is obtained from the various angles at which the object is intersected with a plane. Based on a discriminant method, each of the curves is classified as a parabola, circle, ellipse, hyperbola, or a line. Each quadric surface is shown to be uniquely characterized by a set of these two-dimensional curves, thus allowing discrimination from the others. Before the recognition process can be implemented, the range data have to undergo a set of pre-processing operations, thereby making it more presentable to classification algorithms. One such pre-processing step is to study the effect of median filtering on raw range images. Utilizing a variety of surface curvature techniques, reliable sets of image data that approximate the shape of a quadric surface are determined. Since the initial orientation of the surfaces is unknown, a new technique is developed wherein all the rotation parameters are determined and subsequently eliminated. This approach enables us to position the quadric surfaces in a desired coordinate system. Experiments were conducted on raw range images of spheres, cylinders, and cones. Experiments were also performed on simulated data for surfaces such as hyperboloids of one and two sheets, elliptical and hyperbolic paraboloids, elliptical and hyperbolic cylinders, ellipsoids and the quadric cones. Both the real and simulated data yielded excellent results. Our approach is found to be more accurate and computationally inexpensive as compared to traditional approaches, such as the three-dimensional discriminant approach which involves evaluation of the rank of a matrix.

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

Are face representations depth cue invariant?

PubMed

Dehmoobadsharifabadi, Armita; Farivar, Reza

2016-06-01

The visual system can process three-dimensional depth cues defining surfaces of objects, but it is unclear whether such information contributes to complex object recognition, including face recognition. The processing of different depth cues involves both dorsal and ventral visual pathways. We investigated whether facial surfaces defined by individual depth cues resulted in meaningful face representations-representations that maintain the relationship between the population of faces as defined in a multidimensional face space. We measured face identity aftereffects for facial surfaces defined by individual depth cues (Experiments 1 and 2) and tested whether the aftereffect transfers across depth cues (Experiments 3 and 4). Facial surfaces and their morphs to the average face were defined purely by one of shading, texture, motion, or binocular disparity. We obtained identification thresholds for matched (matched identity between adapting and test stimuli), non-matched (non-matched identity between adapting and test stimuli), and no-adaptation (showing only the test stimuli) conditions for each cue and across different depth cues. We found robust face identity aftereffect in both experiments. Our results suggest that depth cues do contribute to forming meaningful face representations that are depth cue invariant. Depth cue invariance would require integration of information across different areas and different pathways for object recognition, and this in turn has important implications for cortical models of visual object recognition.

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

PubMed

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

2006-10-01

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

3-Dimensional Scene Perception during Active Electrolocation in a Weakly Electric Pulse Fish

PubMed Central

von der Emde, Gerhard; Behr, Katharina; Bouton, Béatrice; Engelmann, Jacob; Fetz, Steffen; Folde, Caroline

2010-01-01

Weakly electric fish use active electrolocation for object detection and orientation in their environment even in complete darkness. The African mormyrid Gnathonemus petersii can detect object parameters, such as material, size, shape, and distance. Here, we tested whether individuals of this species can learn to identify 3-dimensional objects independently of the training conditions and independently of the object's position in space (rotation-invariance; size-constancy). Individual G. petersii were trained in a two-alternative forced-choice procedure to electrically discriminate between a 3-dimensional object (S+) and several alternative objects (S−). Fish were then tested whether they could identify the S+ among novel objects and whether single components of S+ were sufficient for recognition. Size-constancy was investigated by presenting the S+ together with a larger version at different distances. Rotation-invariance was tested by rotating S+ and/or S− in 3D. Our results show that electrolocating G. petersii could (1) recognize an object independently of the S− used during training. When only single components of a complex S+ were offered, recognition of S+ was more or less affected depending on which part was used. (2) Object-size was detected independently of object distance, i.e. fish showed size-constancy. (3) The majority of the fishes tested recognized their S+ even if it was rotated in space, i.e. these fishes showed rotation-invariance. (4) Object recognition was restricted to the near field around the fish and failed when objects were moved more than about 4 cm away from the animals. Our results indicate that even in complete darkness our G. petersii were capable of complex 3-dimensional scene perception using active electrolocation. PMID:20577635

Production of anti-amoxicillin ScFv antibody and simulation studying its molecular recognition mechanism for penicillins.

PubMed

Liu, Jing; Zhang, Hui C; Duan, Chang F; Dong, Jun; Zhao, Guo X; Wang, Jian P; Li, Nan; Liu, Jin Z; Li, Yu W

2016-11-01

The molecular recognition mechanism of an antibody for its hapten is very interesting. The objective of this research was to study the intermolecular interactions of an anti-amoxicillin antibody with penicillin drugs. The single chain variable fragment (ScFv) antibody was generated from a hybridoma cell strain excreting the monoclonal antibody for amoxicillin. The recombinant ScFv antibody showed similar recognition ability for penicillins to its parental monoclonal antibody: simultaneous recognizing 11 penicillins with cross-reactivities of 18-107%. The three-dimensional structure of the ScFv antibody was simulated by using homology modeling, and its intermolecular interactions with 11 penicillins were studied by using molecular docking. Results showed that three CDRs are involved in antibody recognition; CDR L3 Arg 100, CDR H3 Tyr226, and CDR H3 Arg 228 were the key contact amino acid residues; hydrogen bonding was the main antibody-drug intermolecular force; and the core structure of penicillin drugs was the main antibody binding position. These results could explain the recognition mechanism of anti-amoxicillin antibody for amoxicillin and its analogs. This is the first study reporting the production of ScFv antibody for penicillins and stimulation studying its recognition mechanism.

Color Makes a Difference: Two-Dimensional Object Naming in Literate and Illiterate Subjects

ERIC Educational Resources Information Center

Reis, Alexandra; Faisca, Luis; Ingvar, Martin; Petersson, Karl Magnus

2006-01-01

Previous work has shown that illiterate subjects are better at naming two-dimensional representations of real objects when presented as colored photos as compared to black and white drawings. This raises the question if color or textural details selectively improve object recognition and naming in illiterate compared to literate subjects. In this…

Three Dimensional Object Recognition Using a Complex Autoregressive Model

DTIC Science & Technology

1993-12-01

3.4.2 Template Matching Algorithm ...................... 3-16 3.4.3 K-Nearest-Neighbor ( KNN ) Techniques ................. 3-25 3.4.4 Hidden Markov Model...Neighbor ( KNN ) Test Results ...................... 4-13 4.2.1 Single-Look 1-NN Testing .......................... 4-14 4.2.2 Multiple-Look 1-NN Testing...4-15 4.2.3 Discussion of KNN Test Results ...................... 4-15 4.3 Hidden Markov Model (HMM) Test Results

Human action recognition based on point context tensor shape descriptor

NASA Astrophysics Data System (ADS)

Li, Jianjun; Mao, Xia; Chen, Lijiang; Wang, Lan

2017-07-01

Motion trajectory recognition is one of the most important means to determine the identity of a moving object. A compact and discriminative feature representation method can improve the trajectory recognition accuracy. This paper presents an efficient framework for action recognition using a three-dimensional skeleton kinematic joint model. First, we put forward a rotation-scale-translation-invariant shape descriptor based on point context (PC) and the normal vector of hypersurface to jointly characterize local motion and shape information. Meanwhile, an algorithm for extracting the key trajectory based on the confidence coefficient is proposed to reduce the randomness and computational complexity. Second, to decrease the eigenvalue decomposition time complexity, a tensor shape descriptor (TSD) based on PC that can globally capture the spatial layout and temporal order to preserve the spatial information of each frame is proposed. Then, a multilinear projection process is achieved by tensor dynamic time warping to map the TSD to a low-dimensional tensor subspace of the same size. Experimental results show that the proposed shape descriptor is effective and feasible, and the proposed approach obtains considerable performance improvement over the state-of-the-art approaches with respect to accuracy on a public action dataset.

Microoptical compound lens

DOEpatents

Sweatt, William C.; Gill, David D.

2007-10-23

An apposition microoptical compound lens comprises a plurality of lenslets arrayed around a segment of a hollow, three-dimensional optical shell. The lenslets collect light from an object and focus the light rays onto the concentric, curved front surface of a coherent fiber bundle. The fiber bundle transports the light rays to a planar detector, forming a plurality of sub-images that can be reconstructed as a full image. The microoptical compound lens can have a small size (millimeters), wide field of view (up to 180.degree.), and adequate resolution for object recognition and tracking.

Restorative effects of curcumin on sleep-deprivation induced memory impairments and structural changes of the hippocampus in a rat model.

PubMed

Noorafshan, Ali; Karimi, Fatemeh; Kamali, Ali-Mohammad; Karbalay-Doust, Saied; Nami, Mohammad

2017-11-15

The present study examined the consequences of rapid eye-movement sleep-deprivation (REM-SD) with or without curcumin treatment. The outcome measures comprised quantitative features in the three-dimensional reconstruction (3DR) CA1 and dentate gyrus in experimental and control animals using stereological procedures. Male rats were arbitrarily assigned to nine groups based on the intervention and treatment administered including: 1-cage control+distilled water, 2-cage control+curcumin (100mg/kg/day), 3-cage control+olive oil, 4-REM-SD+distilled water, 5-REM-SD+curcumin, 6-REM-SD+olive oil, 7-grid-floor control+distilled water, 8-grid-floor control+curcumin, and 9-grid-floor control+olive oil. Animals in the latter three groups were placed on wire-mesh grids in the sleep-deprivation box. REM-SD was induced by an apparatus comprising a water tank and multiple platforms. After a period of 21days, rats were submitted to the novel object-recognition task. Later, their brains were excised and evaluated using stereological methods. Our results indicated a respective 29% and 31% reduction in the total volume of CA1, and dentate gyrus in REM-SD+distilled water group as compared to the grid-floor control+distilled water group (p<0.05). Other than the above, the overall number of the pyramidal cells of CA1 and granular cells of dentate gyrus in the sleep-deprived group were found to be reduced by 48% and 25%, respectively. The REM-SD+distilled water group also exhibited impaired object recognition memory and deformed three-dimensional reconstructions of these regions. The volume, cell number, reconstruction, object recognition time, and body weight were however recovered in the REM-SD+curcumin compared to the REM-SD+distilled water group. This suggests the potential neuro-restorative effects of curcumin in our model. Copyright © 2017 Elsevier Inc. All rights reserved.

Online 3D Ear Recognition by Combining Global and Local Features.

PubMed

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Online 3D Ear Recognition by Combining Global and Local Features

PubMed Central

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%. PMID:27935955

Assessment of accuracy and recognition of three-dimensional computerized forensic craniofacial reconstruction.

PubMed

Miranda, Geraldo Elias; Wilkinson, Caroline; Roughley, Mark; Beaini, Thiago Leite; Melani, Rodolfo Francisco Haltenhoff

2018-01-01

Facial reconstruction is a technique that aims to reproduce the individual facial characteristics based on interpretation of the skull, with the objective of recognition leading to identification. The aim of this paper was to evaluate the accuracy and recognition level of three-dimensional (3D) computerized forensic craniofacial reconstruction (CCFR) performed in a blind test on open-source software using computed tomography (CT) data from live subjects. Four CCFRs were produced by one of the researchers, who was provided with information concerning the age, sex, and ethnic group of each subject. The CCFRs were produced using Blender® with 3D models obtained from the CT data and templates from the MakeHuman® program. The evaluation of accuracy was carried out in CloudCompare, by geometric comparison of the CCFR to the subject 3D face model (obtained from the CT data). A recognition level was performed using the Picasa® recognition tool with a frontal standardized photography, images of the subject CT face model and the CCFR. Soft-tissue depth and nose, ears and mouth were based on published data, observing Brazilian facial parameters. The results were presented from all the points that form the CCFR model, with an average for each comparison between 63% and 74% with a distance -2.5 ≤ x ≤ 2.5 mm from the skin surface. The average distances were 1.66 to 0.33 mm and greater distances were observed around the eyes, cheeks, mental and zygomatic regions. Two of the four CCFRs were correctly matched by the Picasa® tool. Free software programs are capable of producing 3D CCFRs with plausible levels of accuracy and recognition and therefore indicate their value for use in forensic applications.

Assessment of accuracy and recognition of three-dimensional computerized forensic craniofacial reconstruction

PubMed Central

Wilkinson, Caroline; Roughley, Mark; Beaini, Thiago Leite; Melani, Rodolfo Francisco Haltenhoff

2018-01-01

Facial reconstruction is a technique that aims to reproduce the individual facial characteristics based on interpretation of the skull, with the objective of recognition leading to identification. The aim of this paper was to evaluate the accuracy and recognition level of three-dimensional (3D) computerized forensic craniofacial reconstruction (CCFR) performed in a blind test on open-source software using computed tomography (CT) data from live subjects. Four CCFRs were produced by one of the researchers, who was provided with information concerning the age, sex, and ethnic group of each subject. The CCFRs were produced using Blender® with 3D models obtained from the CT data and templates from the MakeHuman® program. The evaluation of accuracy was carried out in CloudCompare, by geometric comparison of the CCFR to the subject 3D face model (obtained from the CT data). A recognition level was performed using the Picasa® recognition tool with a frontal standardized photography, images of the subject CT face model and the CCFR. Soft-tissue depth and nose, ears and mouth were based on published data, observing Brazilian facial parameters. The results were presented from all the points that form the CCFR model, with an average for each comparison between 63% and 74% with a distance -2.5 ≤ x ≤ 2.5 mm from the skin surface. The average distances were 1.66 to 0.33 mm and greater distances were observed around the eyes, cheeks, mental and zygomatic regions. Two of the four CCFRs were correctly matched by the Picasa® tool. Free software programs are capable of producing 3D CCFRs with plausible levels of accuracy and recognition and therefore indicate their value for use in forensic applications. PMID:29718983

Efficient local representations for three-dimensional palmprint recognition

NASA Astrophysics Data System (ADS)

Yang, Bing; Wang, Xiaohua; Yao, Jinliang; Yang, Xin; Zhu, Wenhua

2013-10-01

Palmprints have been broadly used for personal authentication because they are highly accurate and incur low cost. Most previous works have focused on two-dimensional (2-D) palmprint recognition in the past decade. Unfortunately, 2-D palmprint recognition systems lose the shape information when capturing palmprint images. Moreover, such 2-D palmprint images can be easily forged or affected by noise. Hence, three-dimensional (3-D) palmprint recognition has been regarded as a promising way to further improve the performance of palmprint recognition systems. We have developed a simple, but efficient method for 3-D palmprint recognition by using local features. We first utilize shape index representation to describe the geometry of local regions in 3-D palmprint data. Then, we extract local binary pattern and Gabor wavelet features from the shape index image. The two types of complementary features are finally fused at a score level for further improvements. The experimental results on the Hong Kong Polytechnic 3-D palmprint database, which contains 8000 samples from 400 palms, illustrate the effectiveness of the proposed method.

Three-dimensional fingerprint recognition by using convolution neural network

NASA Astrophysics Data System (ADS)

Tian, Qianyu; Gao, Nan; Zhang, Zonghua

2018-01-01

With the development of science and technology and the improvement of social information, fingerprint recognition technology has become a hot research direction and been widely applied in many actual fields because of its feasibility and reliability. The traditional two-dimensional (2D) fingerprint recognition method relies on matching feature points. This method is not only time-consuming, but also lost three-dimensional (3D) information of fingerprint, with the fingerprint rotation, scaling, damage and other issues, a serious decline in robustness. To solve these problems, 3D fingerprint has been used to recognize human being. Because it is a new research field, there are still lots of challenging problems in 3D fingerprint recognition. This paper presents a new 3D fingerprint recognition method by using a convolution neural network (CNN). By combining 2D fingerprint and fingerprint depth map into CNN, and then through another CNN feature fusion, the characteristics of the fusion complete 3D fingerprint recognition after classification. This method not only can preserve 3D information of fingerprints, but also solves the problem of CNN input. Moreover, the recognition process is simpler than traditional feature point matching algorithm. 3D fingerprint recognition rate by using CNN is compared with other fingerprint recognition algorithms. The experimental results show that the proposed 3D fingerprint recognition method has good recognition rate and robustness.

Variety of geologic silhouette shapes distinguishable by multiple rotations method of quantitative shape analysis text

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

Collins, D.G.; Parks, J.M.

1984-04-01

Silhouette shapes are two-dimensional projections of three-dimensional objects such as sand grains, gravel, and fossils. Within-the-margin markings such as chamber boundaries, sutures, or ribs are ignored. Comparisons between populations of objects from similar and differential origins (i.e., environments, species or genera, growth series, etc) is aided by quantifying the shapes. The Multiple Rotations Method (MRM) uses a variation of ''eigenshapes'', which is capable of distinguishing most of the subtle variations that the ''trained eye'' can detect. With a video-digitizer and microcomputer, MRM is fast, more accurate, and more objective than the human eye. The resulting shape descriptors comprise 5 ormore » 6 numbers per object that can be stored and retrieved to compare with similar descriptions of other objects. The original-shape outlines can be reconstituted sufficiently for gross recognition from these few numerical descriptors. Thus, a semi-automated data-retrieval system becomes feasible, with silhouette-shape descriptions as one of several recognition criteria. MRM consists of four ''rotations'': rotation about a center to a comparable orientation; a principal-components rotation to reduce the many original shape descriptors to a few; a VARIMAX orthogonal-factor rotation to achieve simple structure; and a rotation to achieve factor scores on individual objects. A variety of subtly different shapes includes sand grains from several locations, ages, and environments, and fossils of several types. This variety illustrates the feasibility of quantitative comparisons by MRM.« less

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

PubMed

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

2016-11-01

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

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

An evaluation of three-dimensional sensors for the extravehicular activity helper/retreiver

NASA Technical Reports Server (NTRS)

Magee, Michael

1993-01-01

The Extravehicular Activity Retriever/Helper (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, accurate sensing of the operational environment and objects in the environment will therefore be critical. The qualitative and quantitative results of empirical studies of three sensors that are capable of providing three-dimensional information to the EVAHR, but using completely different hardware approaches are documented. The first of these devices is a phase shift laser with an effective operating range (ambiguity interval) of approximately 15 meters. The second sensor is a laser triangulation system designed to operate at much closer range and to provide higher resolution images. The third sensor is a dual camera stereo imaging system from which range images can also be obtained. The remainder of the report characterizes the strengths and weaknesses of each of these systems relative to quality of data extracted and how different object characteristics affect sensor operation.

Rotation And Scale Invariant Object Recognition Using A Distributed Associative Memory

NASA Astrophysics Data System (ADS)

Wechsler, Harry; Zimmerman, George Lee

1988-04-01

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

Sparse aperture 3D passive image sensing and recognition

NASA Astrophysics Data System (ADS)

Daneshpanah, Mehdi

The way we perceive, capture, store, communicate and visualize the world has greatly changed in the past century Novel three dimensional (3D) imaging and display systems are being pursued both in academic and industrial settings. In many cases, these systems have revolutionized traditional approaches and/or enabled new technologies in other disciplines including medical imaging and diagnostics, industrial metrology, entertainment, robotics as well as defense and security. In this dissertation, we focus on novel aspects of sparse aperture multi-view imaging systems and their application in quantum-limited object recognition in two separate parts. In the first part, two concepts are proposed. First a solution is presented that involves a generalized framework for 3D imaging using randomly distributed sparse apertures. Second, a method is suggested to extract the profile of objects in the scene through statistical properties of the reconstructed light field. In both cases, experimental results are presented that demonstrate the feasibility of the techniques. In the second part, the application of 3D imaging systems in sensing and recognition of objects is addressed. In particular, we focus on the scenario in which only 10s of photons reach the sensor from the object of interest, as opposed to hundreds of billions of photons in normal imaging conditions. At this level, the quantum limited behavior of light will dominate and traditional object recognition practices may fail. We suggest a likelihood based object recognition framework that incorporates the physics of sensing at quantum-limited conditions. Sensor dark noise has been modeled and taken into account. This framework is applied to 3D sensing of thermal objects using visible spectrum detectors. Thermal objects as cold as 250K are shown to provide enough signature photons to be sensed and recognized within background and dark noise with mature, visible band, image forming optics and detector arrays. The results suggest that one might not need to venture into exotic and expensive detector arrays and associated optics for sensing room-temperature thermal objects in complete darkness.

Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models Using Deep Three-Dimensional Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Mano, Tomohiro; Ohtsuki, Tomi

2017-11-01

The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization-localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016), 86, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center.

Subjectively Interpreted Shape Dimensions as Privileged and Orthogonal Axes in Mental Shape Space

ERIC Educational Resources Information Center

Ons, Bart; De Baene, Wouter; Wagemans, Johan

2011-01-01

The shape of an object is fundamental in object recognition but it is still an open issue to what extent shape differences are perceived analytically (i.e., by the dimensional structure of the shapes) or holistically (i.e., by the overall similarity of the shapes). The dimensional structure of a stimulus is available in a primary stage of…

The programming language HAL: A specification

NASA Technical Reports Server (NTRS)

1971-01-01

HAL accomplishes three significant objectives: (1) increased readability, through the use of a natural two-dimensional mathematical format; (2) increased reliability, by providing for selective recognition of common data and subroutines, and by incorporating specific data-protect features; (3) real-time control facility, by including a comprehensive set of real-time control commands and signal conditions. Although HAL is designed primarily for programming on-board computers, it is general enough to meet nearly all the needs in the production, verification and support of aerospace, and other real-time applications.

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction

PubMed Central

Li, Zhongke; Yang, Huifang; Lü, Peijun; Wang, Yong; Sun, Yuchun

2015-01-01

Background and Objective To develop a real-time recording system based on computer binocular vision and two-dimensional image feature extraction to accurately record mandibular movement in three dimensions. Methods A computer-based binocular vision device with two digital cameras was used in conjunction with a fixed head retention bracket to track occlusal movement. Software was developed for extracting target spatial coordinates in real time based on two-dimensional image feature recognition. A plaster model of a subject’s upper and lower dentition were made using conventional methods. A mandibular occlusal splint was made on the plaster model, and then the occlusal surface was removed. Temporal denture base resin was used to make a 3-cm handle extending outside the mouth connecting the anterior labial surface of the occlusal splint with a detection target with intersecting lines designed for spatial coordinate extraction. The subject's head was firmly fixed in place, and the occlusal splint was fully seated on the mandibular dentition. The subject was then asked to make various mouth movements while the mandibular movement target locus point set was recorded. Comparisons between the coordinate values and the actual values of the 30 intersections on the detection target were then analyzed using paired t-tests. Results The three-dimensional trajectory curve shapes of the mandibular movements were consistent with the respective subject movements. Mean XYZ coordinate values and paired t-test results were as follows: X axis: -0.0037 ± 0.02953, P = 0.502; Y axis: 0.0037 ± 0.05242, P = 0.704; and Z axis: 0.0007 ± 0.06040, P = 0.952. The t-test result showed that the coordinate values of the 30 cross points were considered statistically no significant. (P<0.05) Conclusions Use of a real-time recording system of three-dimensional mandibular movement based on computer binocular vision and two-dimensional image feature recognition technology produced a recording accuracy of approximately ± 0.1 mm, and is therefore suitable for clinical application. Certainly, further research is necessary to confirm the clinical applications of the method. PMID:26375800

Biometric identification

NASA Astrophysics Data System (ADS)

Syryamkim, V. I.; Kuznetsov, D. N.; Kuznetsova, A. S.

2018-05-01

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space.

Three-dimensional deformable-model-based localization and recognition of road vehicles.

PubMed

Zhang, Zhaoxiang; Tan, Tieniu; Huang, Kaiqi; Wang, Yunhong

2012-01-01

We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D deformable vehicle model with 12 shape parameters is set up as prior information, and its pose is determined by three parameters, which are its position on the ground plane and its orientation about the vertical axis under ground-plane constraints. An efficient local gradient-based method is proposed to evaluate the fitness between the projection of the vehicle model and image data, which is combined into a novel evolutionary computing framework to estimate the 12 shape parameters and three pose parameters by iterative evolution. The recovery of pose parameters achieves vehicle localization, whereas the shape parameters are used for vehicle recognition. Numerous experiments are conducted in this paper to demonstrate the performance of our approach. It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data. The evolutionary computing framework is effective for vehicles of different types and poses is robust to all kinds of occlusion.

Robust Radar Emitter Recognition Based on the Three-Dimensional Distribution Feature and Transfer Learning

PubMed Central

Yang, Zhutian; Qiu, Wei; Sun, Hongjian; Nallanathan, Arumugam

2016-01-01

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for radar emitter signal recognition. To address this challenge, multi-component radar emitter recognition under a complicated noise environment is studied in this paper. A novel radar emitter recognition approach based on the three-dimensional distribution feature and transfer learning is proposed. The cubic feature for the time-frequency-energy distribution is proposed to describe the intra-pulse modulation information of radar emitters. Furthermore, the feature is reconstructed by using transfer learning in order to obtain the robust feature against signal noise rate (SNR) variation. Last, but not the least, the relevance vector machine is used to classify radar emitter signals. Simulations demonstrate that the approach proposed in this paper has better performances in accuracy and robustness than existing approaches. PMID:26927111

Robust Radar Emitter Recognition Based on the Three-Dimensional Distribution Feature and Transfer Learning.

PubMed

Yang, Zhutian; Qiu, Wei; Sun, Hongjian; Nallanathan, Arumugam

2016-02-25

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for radar emitter signal recognition. To address this challenge, multi-component radar emitter recognition under a complicated noise environment is studied in this paper. A novel radar emitter recognition approach based on the three-dimensional distribution feature and transfer learning is proposed. The cubic feature for the time-frequency-energy distribution is proposed to describe the intra-pulse modulation information of radar emitters. Furthermore, the feature is reconstructed by using transfer learning in order to obtain the robust feature against signal noise rate (SNR) variation. Last, but not the least, the relevance vector machine is used to classify radar emitter signals. Simulations demonstrate that the approach proposed in this paper has better performances in accuracy and robustness than existing approaches.

Posterior Parietal Cortex Drives Inferotemporal Activations During Three-Dimensional Object Vision.

PubMed

Van Dromme, Ilse C; Premereur, Elsie; Verhoef, Bram-Ernst; Vanduffel, Wim; Janssen, Peter

2016-04-01

The primate visual system consists of a ventral stream, specialized for object recognition, and a dorsal visual stream, which is crucial for spatial vision and actions. However, little is known about the interactions and information flow between these two streams. We investigated these interactions within the network processing three-dimensional (3D) object information, comprising both the dorsal and ventral stream. Reversible inactivation of the macaque caudal intraparietal area (CIP) during functional magnetic resonance imaging (fMRI) reduced fMRI activations in posterior parietal cortex in the dorsal stream and, surprisingly, also in the inferotemporal cortex (ITC) in the ventral visual stream. Moreover, CIP inactivation caused a perceptual deficit in a depth-structure categorization task. CIP-microstimulation during fMRI further suggests that CIP projects via posterior parietal areas to the ITC in the ventral stream. To our knowledge, these results provide the first causal evidence for the flow of visual 3D information from the dorsal stream to the ventral stream, and identify CIP as a key area for depth-structure processing. Thus, combining reversible inactivation and electrical microstimulation during fMRI provides a detailed view of the functional interactions between the two visual processing streams.

Posterior Parietal Cortex Drives Inferotemporal Activations During Three-Dimensional Object Vision

PubMed Central

Van Dromme, Ilse C.; Premereur, Elsie; Verhoef, Bram-Ernst; Vanduffel, Wim; Janssen, Peter

2016-01-01

The primate visual system consists of a ventral stream, specialized for object recognition, and a dorsal visual stream, which is crucial for spatial vision and actions. However, little is known about the interactions and information flow between these two streams. We investigated these interactions within the network processing three-dimensional (3D) object information, comprising both the dorsal and ventral stream. Reversible inactivation of the macaque caudal intraparietal area (CIP) during functional magnetic resonance imaging (fMRI) reduced fMRI activations in posterior parietal cortex in the dorsal stream and, surprisingly, also in the inferotemporal cortex (ITC) in the ventral visual stream. Moreover, CIP inactivation caused a perceptual deficit in a depth-structure categorization task. CIP-microstimulation during fMRI further suggests that CIP projects via posterior parietal areas to the ITC in the ventral stream. To our knowledge, these results provide the first causal evidence for the flow of visual 3D information from the dorsal stream to the ventral stream, and identify CIP as a key area for depth-structure processing. Thus, combining reversible inactivation and electrical microstimulation during fMRI provides a detailed view of the functional interactions between the two visual processing streams. PMID:27082854

Study of optical design of three-dimensional digital ophthalmoscopes.

PubMed

Fang, Yi-Chin; Yen, Chih-Ta; Chu, Chin-Hsien

2015-10-01

This study primarily involves using optical zoom structures to design a three-dimensional (3D) human-eye optical sensory system with infrared and visible light. According to experimental data on two-dimensional (2D) and 3D images, human-eye recognition of 3D images is substantially higher (approximately 13.182%) than that of 2D images. Thus, 3D images are more effective than 2D images when they are used at work or in high-recognition devices. In the optical system design, infrared and visible light wavebands were incorporated as light sources to perform simulations. The results can be used to facilitate the design of optical systems suitable for 3D digital ophthalmoscopes.

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.

Image registration under translation and rotation in two-dimensional planes using Fourier slice theorem.

PubMed

Pohit, M; Sharma, J

2015-05-10

Image recognition in the presence of both rotation and translation is a longstanding problem in correlation pattern recognition. Use of log polar transform gives a solution to this problem, but at a cost of losing the vital phase information from the image. The main objective of this paper is to develop an algorithm based on Fourier slice theorem for measuring the simultaneous rotation and translation of an object in a 2D plane. The algorithm is applicable for any arbitrary object shift for full 180° rotation.

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.…

Score-level fusion of two-dimensional and three-dimensional palmprint for personal recognition systems

NASA Astrophysics Data System (ADS)

Chaa, Mourad; Boukezzoula, Naceur-Eddine; Attia, Abdelouahab

2017-01-01

Two types of scores extracted from two-dimensional (2-D) and three-dimensional (3-D) palmprint for personal recognition systems are merged, introducing a local image descriptor for 2-D palmprint-based recognition systems, named bank of binarized statistical image features (B-BSIF). The main idea of B-BSIF is that the extracted histograms from the binarized statistical image features (BSIF) code images (the results of applying the different BSIF descriptor size with the length 12) are concatenated into one to produce a large feature vector. 3-D palmprint contains the depth information of the palm surface. The self-quotient image (SQI) algorithm is applied for reconstructing illumination-invariant 3-D palmprint images. To extract discriminative Gabor features from SQI images, Gabor wavelets are defined and used. Indeed, the dimensionality reduction methods have shown their ability in biometrics systems. Given this, a principal component analysis (PCA)+linear discriminant analysis (LDA) technique is employed. For the matching process, the cosine Mahalanobis distance is applied. Extensive experiments were conducted on a 2-D and 3-D palmprint database with 10,400 range images from 260 individuals. Then, a comparison was made between the proposed algorithm and other existing methods in the literature. Results clearly show that the proposed framework provides a higher correct recognition rate. Furthermore, the best results were obtained by merging the score of B-BSIF descriptor with the score of the SQI+Gabor wavelets+PCA+LDA method, yielding an equal error rate of 0.00% and a recognition rate of rank-1=100.00%.

General tensor discriminant analysis and gabor features for gait recognition.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2007-10-01

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine state of the art classification methods in gait recognition.

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Computer vision

NASA Technical Reports Server (NTRS)

Gennery, D.; Cunningham, R.; Saund, E.; High, J.; Ruoff, C.

1981-01-01

The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed. The representation of such features as texture, edges, curves, and corners are detailed. Recognition methods are described in which cross correlation coefficients are maximized or numerical values for a set of features are measured. Object tracking is discussed in terms of the robust matching algorithms that must be devised. Stereo vision, camera control and calibration, and the hardware and systems architecture are discussed.

The development, assessment and validation of virtual reality for human anatomy instruction

NASA Technical Reports Server (NTRS)

Marshall, Karen Benn

1996-01-01

This research project seeks to meet the objective of science training by developing, assessing, validating and utilizing VR as a human anatomy training medium. Current anatomy instruction is primarily in the form of lectures and usage of textbooks. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three-dimensional, unlike the one-dimensional depiction found in textbooks and the two-dimensional depiction found on the computer. Virtual reality allows one to step through the computer screen into a 3-D artificial world. The primary objective of this project is to produce a virtual reality application of the abdominopelvic region of a human cadaver that can be taken back to the classroom. The hypothesis is that an immersive learning environment affords quicker anatomic recognition and orientation and a greater level of retention in human anatomy instruction. The goal is to augment not replace traditional modes of instruction.

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.

Evidence for perceptual deficits in associative visual (prosop)agnosia: a single-case study.

PubMed

Delvenne, Jean François; Seron, Xavier; Coyette, Françoise; Rossion, Bruno

2004-01-01

Associative visual agnosia is classically defined as normal visual perception stripped of its meaning [Archiv für Psychiatrie und Nervenkrankheiten 21 (1890) 22/English translation: Cognitive Neuropsychol. 5 (1988) 155]: these patients cannot access to their stored visual memories to categorize the objects nonetheless perceived correctly. However, according to an influential theory of visual agnosia [Farah, Visual Agnosia: Disorders of Object Recognition and What They Tell Us about Normal Vision, MIT Press, Cambridge, MA, 1990], visual associative agnosics necessarily present perceptual deficits that are the cause of their impairment at object recognition Here we report a detailed investigation of a patient with bilateral occipito-temporal lesions strongly impaired at object and face recognition. NS presents normal drawing copy, and normal performance at object and face matching tasks as used in classical neuropsychological tests. However, when tested with several computer tasks using carefully controlled visual stimuli and taking both his accuracy rate and response times into account, NS was found to have abnormal performances at high-level visual processing of objects and faces. Albeit presenting a different pattern of deficits than previously described in integrative agnosic patients such as HJA and LH, his deficits were characterized by an inability to integrate individual parts into a whole percept, as suggested by his failure at processing structurally impossible three-dimensional (3D) objects, an absence of face inversion effects and an advantage at detecting and matching single parts. Taken together, these observations question the idea of separate visual representations for object/face perception and object/face knowledge derived from investigations of visual associative (prosop)agnosia, and they raise some methodological issues in the analysis of single-case studies of (prosop)agnosic patients.

Model-Driven Study of Visual Memory

DTIC Science & Technology

2004-12-01

dimensional stimuli (synthetic human faces ) afford important insights into episodic recognition memory. The results were well accommodated by a summed...the unusual properties of the z-transformed ROCS. 15. SUBJECT TERMS Memory, visual memory, computational model, human memory, faces , identity 16...3 Accomplishments/New Findings 3 Work on Objective One: Recognition Memory for Synthetic Faces . 3 Experim ent 1

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 fields. The results of simulation experiments and theory analyzing demonstrate that the proposed method could suppress noise effectively, extracted target edges robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

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

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Pose-Invariant Face Recognition via RGB-D Images.

PubMed

Sang, Gaoli; Li, Jing; Zhao, Qijun

2016-01-01

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

The Impact of Stereoscopic Imagery and Motion on Anatomical Structure Recognition and Visual Attention Performance

ERIC Educational Resources Information Center

Remmele, Martin; Schmidt, Elena; Lingenfelder, Melissa; Martens, Andreas

2018-01-01

Gross anatomy is located in a three-dimensional space. Visualizing aspects of structures in gross anatomy education should aim to provide information that best resembles their original spatial proportions. Stereoscopic three-dimensional imagery might offer possibilities to implement this aim, though some research has revealed potential impairments…

New neural-networks-based 3D object recognition system

NASA Astrophysics Data System (ADS)

Abolmaesumi, Purang; Jahed, M.

1997-09-01

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

3D abnormal behavior recognition in power generation

NASA Astrophysics Data System (ADS)

Wei, Zhenhua; Li, Xuesen; Su, Jie; Lin, Jie

2011-06-01

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and lying down in high place. Taking account of the color and shape are fixed, we adopted edge detecting by color tracking to recognize object in worker. This paper introduces a method, which using geometric character of skeleton and its angle to express sequence of three-dimensional human behavior data. Then adopting Semi-join critical step Hidden Markov Model, weighing probability of critical steps' output to reduce the computational complexity. Training model for every behavior, mean while select some skeleton frames from 3D behavior sample to form a critical step set. This set is a bridge linking 2D observation behavior with 3D human joints feature. The 3D reconstruction is not required during the 2D behavior recognition phase. In the beginning of recognition progress, finding the best match for every frame of 2D observed sample in 3D skeleton set. After that, 2D observed skeleton frames sample will be identified as a specifically 3D behavior by behavior-classifier. The effectiveness of the proposed algorithm is demonstrated with experiments in similar power generation environment.

Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex.

PubMed Central

Malach, R; Reppas, J B; Benson, R R; Kwong, K K; Jiang, H; Kennedy, W A; Ledden, P J; Brady, T J; Rosen, B R; Tootell, R B

1995-01-01

The stages of integration leading from local feature analysis to object recognition were explored in human visual cortex by using the technique of functional magnetic resonance imaging. Here we report evidence for object-related activation. Such activation was located at the lateral-posterior aspect of the occipital lobe, just abutting the posterior aspect of the motion-sensitive area MT/V5, in a region termed the lateral occipital complex (LO). LO showed preferential activation to images of objects, compared to a wide range of texture patterns. This activation was not caused by a global difference in the Fourier spatial frequency content of objects versus texture images, since object images produced enhanced LO activation compared to textures matched in power spectra but randomized in phase. The preferential activation to objects also could not be explained by different patterns of eye movements: similar levels of activation were observed when subjects fixated on the objects and when they scanned the objects with their eyes. Additional manipulations such as spatial frequency filtering and a 4-fold change in visual size did not affect LO activation. These results suggest that the enhanced responses to objects were not a manifestation of low-level visual processing. A striking demonstration that activity in LO is uniquely correlated to object detectability was produced by the "Lincoln" illusion, in which blurring of objects digitized into large blocks paradoxically increases their recognizability. Such blurring led to significant enhancement of LO activation. Despite the preferential activation to objects, LO did not seem to be involved in the final, "semantic," stages of the recognition process. Thus, objects varying widely in their recognizability (e.g., famous faces, common objects, and unfamiliar three-dimensional abstract sculptures) activated it to a similar degree. These results are thus evidence for an intermediate link in the chain of processing stages leading to object recognition in human visual cortex. Images Fig. 1 Fig. 2 Fig. 3 PMID:7667258

[Identification of perforating vessels by augmented reality: Application for the deep inferior epigastric perforator flap].

PubMed

Bosc, R; Fitoussi, A; Pigneur, F; Tacher, V; Hersant, B; Meningaud, J-P

2017-08-01

The augmented reality on smart glasses allows the surgeon to visualize three-dimensional virtual objects during surgery, superimposed in real time to the anatomy of the patient. This makes it possible to preserve the vision of the surgical field and to dispose of added computerized information without the need to use a physical surgical guide or a deported screen. The three-dimensional objects that we used and visualized in augmented reality came from the reconstructions made from the CT-scans of the patients. These objects have been transferred through a dedicated application on stereoscopic smart glasses. The positioning and the stabilization of the virtual layers on the anatomy of the patients were obtained thanks to the recognition, by the glasses, of a tracker placed on the skin. We used this technology, in addition to the usual locating methods for preoperative planning and the selection of perforating vessels for 12 patients operated on a breast reconstruction, by perforating flap of deep lower epigastric artery. The "hands-free" smart glasses with two stereoscopic screens make it possible to provide the reconstructive surgeon with binocular visualization in the operative field of the vessels identified with the CT-scan. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

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…

Coordinate Transformations in Object Recognition

ERIC Educational Resources Information Center

Graf, Markus

2006-01-01

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

3D Surface Reconstruction for Lower Limb Prosthetic Model using Radon Transform

NASA Astrophysics Data System (ADS)

Sobani, S. S. Mohd; Mahmood, N. H.; Zakaria, N. A.; Razak, M. A. Abdul

2018-03-01

This paper describes the idea to realize three-dimensional surfaces of objects with cylinder-based shapes where the techniques adopted and the strategy developed for a non-rigid three-dimensional surface reconstruction of an object from uncalibrated two-dimensional image sequences using multiple-view digital camera and turntable setup. The surface of an object is reconstructed based on the concept of tomography with the aid of performing several digital image processing algorithms on the two-dimensional images captured by a digital camera in thirty-six different projections and the three-dimensional structure of the surface is analysed. Four different objects are used as experimental models in the reconstructions and each object is placed on a manually rotated turntable. The results shown that the proposed method has successfully reconstruct the three-dimensional surface of the objects and practicable. The shape and size of the reconstructed three-dimensional objects are recognizable and distinguishable. The reconstructions of objects involved in the test are strengthened with the analysis where the maximum percent error obtained from the computation is approximately 1.4 % for the height whilst 4.0%, 4.79% and 4.7% for the diameters at three specific heights of the objects.

Space imaging measurement system based on fixed lens and moving detector

NASA Astrophysics Data System (ADS)

Akiyama, Akira; Doshida, Minoru; Mutoh, Eiichiro; Kumagai, Hideo; Yamada, Hirofumi; Ishii, Hiromitsu

2006-08-01

We have developed the Space Imaging Measurement System based on the fixed lens and fast moving detector to the control of the autonomous ground vehicle. The space measurement is the most important task in the development of the autonomous ground vehicle. In this study we move the detector back and forth along the optical axis at the fast rate to measure the three-dimensional image data. This system is just appropriate to the autonomous ground vehicle because this system does not send out any optical energy to measure the distance and keep the safety. And we use the digital camera of the visible ray range. Therefore it gives us the cost reduction of the three-dimensional image data acquisition with respect to the imaging laser system. We can combine many pieces of the narrow space imaging measurement data to construct the wide range three-dimensional data. This gives us the improvement of the image recognition with respect to the object space. To develop the fast movement of the detector, we build the counter mass balance in the mechanical crank system of the Space Imaging Measurement System. And then we set up the duct to prevent the optical noise due to the ray not coming through lens. The object distance is derived from the focus distance which related to the best focused image data. The best focused image data is selected from the image of the maximum standard deviation in the standard deviations of series images.

Sonic morphology: Aesthetic dimensional auditory spatial awareness

NASA Astrophysics Data System (ADS)

Whitehouse, Martha M.

The sound and ceramic sculpture installation, " Skirting the Edge: Experiences in Sound & Form," is an integration of art and science demonstrating the concept of sonic morphology. "Sonic morphology" is herein defined as aesthetic three-dimensional auditory spatial awareness. The exhibition explicates my empirical phenomenal observations that sound has a three-dimensional form. Composed of ceramic sculptures that allude to different social and physical situations, coupled with sound compositions that enhance and create a three-dimensional auditory and visual aesthetic experience (see accompanying DVD), the exhibition supports the research question, "What is the relationship between sound and form?" Precisely how people aurally experience three-dimensional space involves an integration of spatial properties, auditory perception, individual history, and cultural mores. People also utilize environmental sound events as a guide in social situations and in remembering their personal history, as well as a guide in moving through space. Aesthetically, sound affects the fascination, meaning, and attention one has within a particular space. Sonic morphology brings art forms such as a movie, video, sound composition, and musical performance into the cognitive scope by generating meaning from the link between the visual and auditory senses. This research examined sonic morphology as an extension of musique concrete, sound as object, originating in Pierre Schaeffer's work in the 1940s. Pointing, as John Cage did, to the corporeal three-dimensional experience of "all sound," I composed works that took their total form only through the perceiver-participant's participation in the exhibition. While contemporary artist Alvin Lucier creates artworks that draw attention to making sound visible, "Skirting the Edge" engages the perceiver-participant visually and aurally, leading to recognition of sonic morphology.

Distorted Character Recognition Via An Associative Neural Network

NASA Astrophysics Data System (ADS)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

Visual Object Detection, Categorization, and Identification Tasks Are Associated with Different Time Courses and Sensitivities

ERIC Educational Resources Information Center

de la Rosa, Stephan; Choudhery, Rabia N.; Chatziastros, Astros

2011-01-01

Recent evidence suggests that the recognition of an object's presence and its explicit recognition are temporally closely related. Here we re-examined the time course (using a fine and a coarse temporal resolution) and the sensitivity of three possible component processes of visual object recognition. In particular, participants saw briefly…

Object Scene Flow

NASA Astrophysics Data System (ADS)

Menze, Moritz; Heipke, Christian; Geiger, Andreas

2018-06-01

This work investigates the estimation of dense three-dimensional motion fields, commonly referred to as scene flow. While great progress has been made in recent years, large displacements and adverse imaging conditions as observed in natural outdoor environments are still very challenging for current approaches to reconstruction and motion estimation. In this paper, we propose a unified random field model which reasons jointly about 3D scene flow as well as the location, shape and motion of vehicles in the observed scene. We formulate the problem as the task of decomposing the scene into a small number of rigidly moving objects sharing the same motion parameters. Thus, our formulation effectively introduces long-range spatial dependencies which commonly employed local rigidity priors are lacking. Our inference algorithm then estimates the association of image segments and object hypotheses together with their three-dimensional shape and motion. We demonstrate the potential of the proposed approach by introducing a novel challenging scene flow benchmark which allows for a thorough comparison of the proposed scene flow approach with respect to various baseline models. In contrast to previous benchmarks, our evaluation is the first to provide stereo and optical flow ground truth for dynamic real-world urban scenes at large scale. Our experiments reveal that rigid motion segmentation can be utilized as an effective regularizer for the scene flow problem, improving upon existing two-frame scene flow methods. At the same time, our method yields plausible object segmentations without requiring an explicitly trained recognition model for a specific object class.

Binocular depth processing in the ventral visual pathway

PubMed Central

Vogels, Rufin

2016-01-01

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269602

Binocular depth processing in the ventral visual pathway.

PubMed

Verhoef, Bram-Ernst; Vogels, Rufin; Janssen, Peter

2016-06-19

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

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

PubMed

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

2000-01-01

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

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

An ERP study of recognition memory for concrete and abstract pictures in school-aged children

PubMed Central

Boucher, Olivier; Chouinard-Leclaire, Christine; Muckle, Gina; Westerlund, Alissa; Burden, Matthew J.; Jacobson, Sandra W.; Jacobson, Joseph L.

2016-01-01

Recognition memory for concrete, nameable pictures is typically faster and more accurate than for abstract pictures. A dual-coding account for these findings suggests that concrete pictures are processed into verbal and image codes, whereas abstract pictures are encoded in image codes only. Recognition memory relies on two successive and distinct processes, namely familiarity and recollection. Whether these two processes are similarly or differently affected by stimulus concreteness remains unknown. This study examined the effect of picture concreteness on visual recognition memory processes using event-related potentials (ERPs). In a sample of children involved in a longitudinal study, participants (N = 96; mean age = 11.3 years) were assessed on a continuous visual recognition memory task in which half the pictures were easily nameable, everyday concrete objects, and the other half were three-dimensional abstract, sculpture-like objects. Behavioral performance and ERP correlates of familiarity and recollection (respectively, the FN400 and P600 repetition effects) were measured. Behavioral results indicated faster and more accurate identification of concrete pictures as “new” or “old” (i.e., previously displayed) compared to abstract pictures. ERPs were characterised by a larger repetition effect, on the P600 amplitude, for concrete than for abstract images, suggesting a graded recollection process dependant on the type of material to be recollected. Topographic differences were observed within the FN400 latency interval, especially over anterior-inferior electrodes, with the repetition effect more pronounced and localized over the left hemisphere for concrete stimuli, potentially reflecting different neural processes underlying early processing of verbal/semantic and visual material in memory. PMID:27329352

Automatic anatomy recognition via multiobject oriented active shape models.

PubMed

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

2010-12-01

This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a recognition accuracy of > or = 90% yielded a TPVF > or = 95% and FPVF < or = 0.5%. Over the three data sets and over all tested objects, in 97% of the cases, the optimal solutions found by the proposed method constituted the true global optimum. The experimental results showed the feasibility and efficacy of the proposed automatic anatomy recognition system. Increasing the number of objects in the model can significantly improve both recognition and delineation accuracy. More spread out arrangement of objects in the model can lead to improved recognition and delineation accuracy. Including larger objects in the model also improved recognition and delineation. The proposed method almost always finds globally optimum solutions.

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

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

The use of global image characteristics for neural network pattern recognitions

NASA Astrophysics Data System (ADS)

Kulyas, Maksim O.; Kulyas, Oleg L.; Loshkarev, Aleksey S.

2017-04-01

The recognition system is observed, where the information is transferred by images of symbols generated by a television camera. For descriptors of objects the coefficients of two-dimensional Fourier transformation generated in a special way. For solution of the task of classification the one-layer neural network trained on reference images is used. Fast learning of a neural network with a single neuron calculation of coefficients is applied.

Effects of Two and Three-Dimensional Visual Objects on the Acquisition of Drawing Skills among JSS1 Students in Osun State, Nigeria

ERIC Educational Resources Information Center

Abass, Bada Tayo; Isyakka, Bello; Olaolu, Ijisakin Yemi; Olusegun, Fajuyigbe Michael

2014-01-01

The study examined the effects of two and three dimensional visual objects on learners' drawing skills in junior secondary schools in OsunState, Nigeria. It also determined students' ability to identify visual objects. Furthermore, it investigated the comparative effectiveness of two and three dimensional visual objects on drawing skills of junior…

Three-Dimensional Object Recognition and Registration for Robotic Grasping Systems Using a Modified Viewpoint Feature Histogram

PubMed Central

Chen, Chin-Sheng; Chen, Po-Chun; Hsu, Chih-Ming

2016-01-01

This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. PMID:27886080

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

Unconstrained handwritten numeral recognition based on radial basis competitive and cooperative networks with spatio-temporal feature representation.

PubMed

Lee, S; Pan, J J

1996-01-01

This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.

Face recognition from unconstrained three-dimensional face images using multitask sparse representation

NASA Astrophysics Data System (ADS)

Bentaieb, Samia; Ouamri, Abdelaziz; Nait-Ali, Amine; Keche, Mokhtar

2018-01-01

We propose and evaluate a three-dimensional (3D) face recognition approach that applies the speeded up robust feature (SURF) algorithm to the depth representation of shape index map, under real-world conditions, using only a single gallery sample for each subject. First, the 3D scans are preprocessed, then SURF is applied on the shape index map to find interest points and their descriptors. Each 3D face scan is represented by keypoints descriptors, and a large dictionary is built from all the gallery descriptors. At the recognition step, descriptors of a probe face scan are sparsely represented by the dictionary. A multitask sparse representation classification is used to determine the identity of each probe face. The feasibility of the approach that uses the SURF algorithm on the shape index map for face identification/authentication is checked through an experimental investigation conducted on Bosphorus, University of Milano Bicocca, and CASIA 3D datasets. It achieves an overall rank one recognition rate of 97.75%, 80.85%, and 95.12%, respectively, on these datasets.

Infant visual attention and object recognition.

PubMed

Reynolds, Greg D

2015-05-15

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

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

How Young Children and Chimpanzees ("Pan Troglodytes") Perceive Objects in a 2D Display: Putting an Assumption to the Test

ERIC Educational Resources Information Center

Leighty, Katherine A.; Menzel, Charles R.; Fragaszy, Dorothy M.

2008-01-01

Object recognition research is typically conducted using 2D stimuli in lieu of 3D objects. This study investigated the amount and complexity of knowledge gained from 2D stimuli in adult chimpanzees ("Pan troglodytes") and young children (aged 3 and 4 years) using a titrated series of cross-dimensional search tasks. Results indicate that 3-year-old…

Good Practices for Learning to Recognize Actions Using FV and VLAD.

PubMed

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

Iris recognition via plenoptic imaging

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

Santos-Villalobos, Hector J.; Boehnen, Chris Bensing; Bolme, David S.

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios.

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

An ERP study of recognition memory for concrete and abstract pictures in school-aged children.

PubMed

Boucher, Olivier; Chouinard-Leclaire, Christine; Muckle, Gina; Westerlund, Alissa; Burden, Matthew J; Jacobson, Sandra W; Jacobson, Joseph L

2016-08-01

Recognition memory for concrete, nameable pictures is typically faster and more accurate than for abstract pictures. A dual-coding account for these findings suggests that concrete pictures are processed into verbal and image codes, whereas abstract pictures are encoded in image codes only. Recognition memory relies on two successive and distinct processes, namely familiarity and recollection. Whether these two processes are similarly or differently affected by stimulus concreteness remains unknown. This study examined the effect of picture concreteness on visual recognition memory processes using event-related potentials (ERPs). In a sample of children involved in a longitudinal study, participants (N=96; mean age=11.3years) were assessed on a continuous visual recognition memory task in which half the pictures were easily nameable, everyday concrete objects, and the other half were three-dimensional abstract, sculpture-like objects. Behavioral performance and ERP correlates of familiarity and recollection (respectively, the FN400 and P600 repetition effects) were measured. Behavioral results indicated faster and more accurate identification of concrete pictures as "new" or "old" (i.e., previously displayed) compared to abstract pictures. ERPs were characterized by a larger repetition effect, on the P600 amplitude, for concrete than for abstract images, suggesting a graded recollection process dependent on the type of material to be recollected. Topographic differences were observed within the FN400 latency interval, especially over anterior-inferior electrodes, with the repetition effect more pronounced and localized over the left hemisphere for concrete stimuli, potentially reflecting different neural processes underlying early processing of verbal/semantic and visual material in memory. Copyright © 2016 Elsevier B.V. All rights reserved.

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

Neurocomputational bases of object and face recognition.

PubMed Central

Biederman, I; Kalocsai, P

1997-01-01

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

Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

Recognition memory in tree shrew (Tupaia belangeri) after repeated familiarization sessions.

PubMed

Khani, Abbas; Rainer, Gregor

2012-07-01

Recognition memories are formed during perceptual experience and allow subsequent recognition of previously encountered objects as well as their distinction from novel objects. As a consequence, novel objects are generally explored longer than familiar objects by many species. This novelty preference has been documented in rodents using the novel object recognition (NOR) test, as well is in primates including humans using preferential looking time paradigms. Here, we examine novelty preference using the NOR task in tree shrew, a small animal species that is considered to be an intermediary between rodents and primates. Our paradigm consisted of three phases: arena familiarization, object familiarization sessions with two identical objects in the arena and finally a test session following a 24-h retention period with a familiar and a novel object in the arena. We employed two different object familiarization durations: one and three sessions on consecutive days. After three object familiarization sessions, tree shrews exhibited robust preference for novel objects on the test day. This was accompanied by significant reduction in familiar object exploration time, occurring largely between the first and second day of object familiarization. By contrast, tree shrews did not show a significant preference for the novel object after a one-session object familiarization. Nonetheless, they spent significantly less time exploring the familiar object on the test day compared to the object familiarization day, indicating that they did maintain a memory trace for the familiar object. Our study revealed different time courses for familiar object habituation and emergence of novelty preference, suggesting that novelty preference is dependent on well-consolidated memory of the competing familiar object. Taken together, our results demonstrate robust novelty preference of tree shrews, in general similarity to previous findings in rodents and primates. Copyright © 2012 Elsevier B.V. All rights reserved.

Three-dimensional image acquisition and reconstruction system on a mobile device based on computer-generated integral imaging.

PubMed

Erdenebat, Munkh-Uchral; Kim, Byeong-Jun; Piao, Yan-Ling; Park, Seo-Yeon; Kwon, Ki-Chul; Piao, Mei-Lan; Yoo, Kwan-Hee; Kim, Nam

2017-10-01

A mobile three-dimensional image acquisition and reconstruction system using a computer-generated integral imaging technique is proposed. A depth camera connected to the mobile device acquires the color and depth data of a real object simultaneously, and an elemental image array is generated based on the original three-dimensional information for the object, with lens array specifications input into the mobile device. The three-dimensional visualization of the real object is reconstructed on the mobile display through optical or digital reconstruction methods. The proposed system is implemented successfully and the experimental results certify that the system is an effective and interesting method of displaying real three-dimensional content on a mobile device.

Three-dimensional obstacle classification in laser range data

NASA Astrophysics Data System (ADS)

Armbruster, Walter; Bers, Karl-Heinz

1998-10-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser rangefinders which are presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from wires at over 500 m range (depends on the system) with a high hit-and-detect probability. Despite the efficiency of the sensor, acceptance of current obstacle warning systems by test pilots is not very high, mainly due to the systems' inadequacies in obstacle recognition and visualization. This has motivated the development and the testing of more advanced 3d-scene analysis algorithm at FGAN-FIM to replace the obstacle recognition component of current warning systems. The basic ideas are to increase the recognition probability and to reduce the false alarm rate for hard-to-extract obstacles such as wires, by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. by implementing a hierarchical classification procedure to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Three Dimensional Measurements And Display Using A Robot Arm

NASA Astrophysics Data System (ADS)

Swift, Thomas E.

1984-02-01

The purpose of this paper is to describe a project which makes three dimensional measurements of an object using a robot arm. A program was written to determine the X-Y-Z coordinates of the end point of a Minimover-5 robot arm which was interfaced to a TRS-80 Model III microcomputer. This program was used in conjunction with computer graphics subroutines that draw a projected three dimensional object.. The robot arm was direc-ted to touch points on an object and then lines were drawn on the screen of the microcomputer between consecutive points as they were entered. A representation of the entire object is in this way constructed on the screen. The three dimensional graphics subroutines have the ability to rotate the projected object about any of the three axes, and to scale the object to any size. This project has applications in the computer-aided design and manufacturing fields because it can accurately measure the features of an irregularly shaped object.

Effects of target shape and reflection on laser radar cross sections.

PubMed

Steinvall, O

2000-08-20

Laser radar cross sections have been evaluated for a number of ideal targets such as cones, spheres, paraboloids, and cylinders by use of different reflection characteristics. The time-independent cross section is the ratio of the cross section of one of these forms to that of a plate with the same maximum radius. The time-dependent laser radar cross section involves the impulse response from the object shape multiplied by the beam's transverse profile and the surface bidirectional reflection distribution function. It can be clearly seen that knowledge of the combined effect of object shape and reflection characteristics is important for determining the shape and the magnitude of the laser radar return. The results of this study are of interest for many laser radar applications such as ranging, three-dimensional imaging-modeling, tracking, antisensor lasers, and target recognition.

Online signature recognition using principal component analysis and artificial neural network

NASA Astrophysics Data System (ADS)

Hwang, Seung-Jun; Park, Seung-Je; Baek, Joong-Hwan

2016-12-01

In this paper, we propose an algorithm for on-line signature recognition using fingertip point in the air from the depth image acquired by Kinect. We extract 10 statistical features from X, Y, Z axis, which are invariant to changes in shifting and scaling of the signature trajectories in three-dimensional space. Artificial neural network is adopted to solve the complex signature classification problem. 30 dimensional features are converted into 10 principal components using principal component analysis, which is 99.02% of total variances. We implement the proposed algorithm and test to actual on-line signatures. In experiment, we verify the proposed method is successful to classify 15 different on-line signatures. Experimental result shows 98.47% of recognition rate when using only 10 feature vectors.

Multidimensional brain activity dictated by winner-take-all mechanisms.

PubMed

Tozzi, Arturo; Peters, James F

2018-06-21

A novel demon-based architecture is introduced to elucidate brain functions such as pattern recognition during human perception and mental interpretation of visual scenes. Starting from the topological concepts of invariance and persistence, we introduce a Selfridge pandemonium variant of brain activity that takes into account a novel feature, namely, demons that recognize short straight-line segments, curved lines and scene shapes, such as shape interior, density and texture. Low-level representations of objects can be mapped to higher-level views (our mental interpretations): a series of transformations can be gradually applied to a pattern in a visual scene, without affecting its invariant properties. This makes it possible to construct a symbolic multi-dimensional representation of the environment. These representations can be projected continuously to an object that we have seen and continue to see, thanks to the mapping from shapes in our memory to shapes in Euclidean space. Although perceived shapes are 3-dimensional (plus time), the evaluation of shape features (volume, color, contour, closeness, texture, and so on) leads to n-dimensional brain landscapes. Here we discuss the advantages of our parallel, hierarchical model in pattern recognition, computer vision and biological nervous system's evolution. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2003-01-01

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

Automated sea floor extraction from underwater video

NASA Astrophysics Data System (ADS)

Kelly, Lauren; Rahmes, Mark; Stiver, James; McCluskey, Mike

2016-05-01

Ocean floor mapping using video is a method to simply and cost-effectively record large areas of the seafloor. Obtaining visual and elevation models has noteworthy applications in search and recovery missions. Hazards to navigation are abundant and pose a significant threat to the safety, effectiveness, and speed of naval operations and commercial vessels. This project's objective was to develop a workflow to automatically extract metadata from marine video and create image optical and elevation surface mosaics. Three developments made this possible. First, optical character recognition (OCR) by means of two-dimensional correlation, using a known character set, allowed for the capture of metadata from image files. Second, exploiting the image metadata (i.e., latitude, longitude, heading, camera angle, and depth readings) allowed for the determination of location and orientation of the image frame in mosaic. Image registration improved the accuracy of mosaicking. Finally, overlapping data allowed us to determine height information. A disparity map was created using the parallax from overlapping viewpoints of a given area and the relative height data was utilized to create a three-dimensional, textured elevation map.

Protein structure-structure alignment with discrete Fréchet distance.

PubMed

Jiang, Minghui; Xu, Ying; Zhu, Binhai

2008-02-01

Matching two geometric objects in two-dimensional (2D) and three-dimensional (3D) spaces is a central problem in computer vision, pattern recognition, and protein structure prediction. In particular, the problem of aligning two polygonal chains under translation and rotation to minimize their distance has been studied using various distance measures. It is well known that the Hausdorff distance is useful for matching two point sets, and that the Fréchet distance is a superior measure for matching two polygonal chains. The discrete Fréchet distance closely approximates the (continuous) Fréchet distance, and is a natural measure for the geometric similarity of the folded 3D structures of biomolecules such as proteins. In this paper, we present new algorithms for matching two polygonal chains in two dimensions to minimize their discrete Fréchet distance under translation and rotation, and an effective heuristic for matching two polygonal chains in three dimensions. We also describe our empirical results on the application of the discrete Fréchet distance to protein structure-structure alignment.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

System for optically recognizing and tracking a plurality of objects within a field of vision. Laser (46) produces a coherent beam (48). Beam splitter (24) splits the beam into object (26) and reference (28) beams. Beam expanders (50) and collimators (52) transform the beams (26, 28) into coherent collimated light beams (26', 28'). A two-dimensional SLM (54), disposed in the object beam (26'), modulates the object beam with optical information as a function of signals from a first camera (16) which develops X and Y signals reflecting the contents of its field of vision. A hololens (38), positioned in the object beam (26') subsequent to the modulator (54), focuses the object beam at a plurality of focal points (42). A planar transparency-forming film (32), disposed with the focal points on an exposable surface, forms a multiple position interference filter (62) upon exposure of the surface and development processing of the film (32). A reflector (53) directing the reference beam (28') onto the film (32), exposes the surface, with images focused by the hololens (38), to form interference patterns on the surface. There is apparatus (16', 64) for sensing and indicating light passage through respective ones of the positions of the filter (62), whereby recognition of objects corresponding to respective ones of the positions of the filter (62) is affected. For tracking, apparatus (64) focuses light passing through the filter (62) onto a matrix of CCD's in a second camera (16') to form a two-dimensional display of the recognized objects.

Structured light optical microscopy for three-dimensional reconstruction of technical surfaces

NASA Astrophysics Data System (ADS)

Kettel, Johannes; Reinecke, Holger; Müller, Claas

2016-04-01

In microsystems technology quality control of micro structured surfaces with different surface properties is playing an ever more important role. The process of quality control incorporates three-dimensional (3D) reconstruction of specularand diffusive reflecting technical surfaces. Due to the demand on high measurement accuracy and data acquisition rates, structured light optical microscopy has become a valuable solution to solve this problem providing high vertical and lateral resolution. However, 3D reconstruction of specular reflecting technical surfaces still remains a challenge to optical measurement principles. In this paper we present a measurement principle based on structured light optical microscopy which enables 3D reconstruction of specular- and diffusive reflecting technical surfaces. It is realized using two light paths of a stereo microscope equipped with different magnification levels. The right optical path of the stereo microscope is used to project structured light onto the object surface. The left optical path is used to capture the structured illuminated object surface with a camera. Structured light patterns are generated by a Digital Light Processing (DLP) device in combination with a high power Light Emitting Diode (LED). Structured light patterns are realized as a matrix of discrete light spots to illuminate defined areas on the object surface. The introduced measurement principle is based on multiple and parallel processed point measurements. Analysis of the measured Point Spread Function (PSF) by pattern recognition and model fitting algorithms enables the precise calculation of 3D coordinates. Using exemplary technical surfaces we demonstrate the successful application of our measurement principle.

The three-dimensional Event-Driven Graphics Environment (3D-EDGE)

NASA Technical Reports Server (NTRS)

Freedman, Jeffrey; Hahn, Roger; Schwartz, David M.

1993-01-01

Stanford Telecom developed the Three-Dimensional Event-Driven Graphics Environment (3D-EDGE) for NASA GSFC's (GSFC) Communications Link Analysis and Simulation System (CLASS). 3D-EDGE consists of a library of object-oriented subroutines which allow engineers with little or no computer graphics experience to programmatically manipulate, render, animate, and access complex three-dimensional objects.

Development of Three-Dimensional Completion of Complex Objects

ERIC Educational Resources Information Center

Soska, Kasey C.; Johnson, Scott P.

2013-01-01

Three-dimensional (3D) object completion, the ability to perceive the backs of objects seen from a single viewpoint, emerges at around 6 months of age. Yet, only relatively simple 3D objects have been used in assessing its development. This study examined infants' 3D object completion when presented with more complex stimuli. Infants…

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

What Three-Year-Olds Remember from Their Past: Long-Term Memory for Persons, Objects, and Actions

ERIC Educational Resources Information Center

Hirte, Monika; Graf, Frauke; Kim, Ziyon; Knopf, Monika

2017-01-01

From birth on, infants show long-term recognition memory for persons. Furthermore, infants from six months onwards are able to store and retrieve demonstrated actions over long-term intervals in deferred imitation tasks. Thus, information about the model demonstrating the object-related actions is stored and recognition memory for the objects as…

Recognition of Frequency Modulated Whistle-Like Sounds by a Bottlenose Dolphin (Tursiops truncatus) and Humans with Transformations in Amplitude, Duration and Frequency.

PubMed

Branstetter, Brian K; DeLong, Caroline M; Dziedzic, Brandon; Black, Amy; Bakhtiari, Kimberly

2016-01-01

Bottlenose dolphins (Tursiops truncatus) use the frequency contour of whistles produced by conspecifics for individual recognition. Here we tested a bottlenose dolphin's (Tursiops truncatus) ability to recognize frequency modulated whistle-like sounds using a three alternative matching-to-sample paradigm. The dolphin was first trained to select a specific object (object A) in response to a specific sound (sound A) for a total of three object-sound associations. The sounds were then transformed by amplitude, duration, or frequency transposition while still preserving the frequency contour of each sound. For comparison purposes, 30 human participants completed an identical task with the same sounds, objects, and training procedure. The dolphin's ability to correctly match objects to sounds was robust to changes in amplitude with only a minor decrement in performance for short durations. The dolphin failed to recognize sounds that were frequency transposed by plus or minus ½ octaves. Human participants demonstrated robust recognition with all acoustic transformations. The results indicate that this dolphin's acoustic recognition of whistle-like sounds was constrained by absolute pitch. Unlike human speech, which varies considerably in average frequency, signature whistles are relatively stable in frequency, which may have selected for a whistle recognition system invariant to frequency transposition.

Recognition of Frequency Modulated Whistle-Like Sounds by a Bottlenose Dolphin (Tursiops truncatus) and Humans with Transformations in Amplitude, Duration and Frequency

PubMed Central

Branstetter, Brian K.; DeLong, Caroline M.; Dziedzic, Brandon; Black, Amy; Bakhtiari, Kimberly

2016-01-01

Bottlenose dolphins (Tursiops truncatus) use the frequency contour of whistles produced by conspecifics for individual recognition. Here we tested a bottlenose dolphin’s (Tursiops truncatus) ability to recognize frequency modulated whistle-like sounds using a three alternative matching-to-sample paradigm. The dolphin was first trained to select a specific object (object A) in response to a specific sound (sound A) for a total of three object-sound associations. The sounds were then transformed by amplitude, duration, or frequency transposition while still preserving the frequency contour of each sound. For comparison purposes, 30 human participants completed an identical task with the same sounds, objects, and training procedure. The dolphin’s ability to correctly match objects to sounds was robust to changes in amplitude with only a minor decrement in performance for short durations. The dolphin failed to recognize sounds that were frequency transposed by plus or minus ½ octaves. Human participants demonstrated robust recognition with all acoustic transformations. The results indicate that this dolphin’s acoustic recognition of whistle-like sounds was constrained by absolute pitch. Unlike human speech, which varies considerably in average frequency, signature whistles are relatively stable in frequency, which may have selected for a whistle recognition system invariant to frequency transposition. PMID:26863519

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

PubMed

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

2010-09-01

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

Automatic anatomy recognition on CT images with pathology

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Three-quarter view preference for three-dimensional objects in 8-month-old infants.

PubMed

Yamashita, Wakayo; Niimi, Ryosuke; Kanazawa, So; Yamaguchi, Masami K; Yokosawa, Kazuhiko

2014-04-04

This study examined infants' visual perception of three-dimensional common objects. It has been reported that human adults perceive object images in a view-dependent manner: three-quarter views are often preferred to other views, and the sensitivity to object orientation is lower for three-quarter views than for other views. We tested whether such characteristics were observed in 6- to 8-month-old infants by measuring their preferential looking behavior. In Experiment 1 we examined 190- to 240-day-olds' sensitivity to orientation change and in Experiment 2 we examined these infants' preferential looking for the three-quarter view. The 240-day-old infants showed a pattern of results similar to adults for some objects, while the 190-day-old infants did not. The 240-day-old infants' perception of object view is (partly) similar to that of adults. These results suggest that human visual perception of three-dimensional objects develops at 6 to 8 months of age.

System and method for representing and manipulating three-dimensional objects on massively parallel architectures

DOEpatents

Karasick, Michael S.; Strip, David R.

1996-01-01

A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modelling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modelling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modelling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication.

Palm vein recognition based on directional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

2014-04-01

Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views.

PubMed

Chaaraoui, Alexandros Andre; Flórez-Revuelta, Francisco

2014-01-01

This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.

An Essential Protein Repair Enzyme: Investigation of the Molecular Recognition Mechanism of Methionine Sulfoxide Reductase A

DTIC Science & Technology

2008-05-01

4 ). The three-dimensional spatial orientation of the atoms for these resolved solution structures (Protein Data Bank accession codes: 2gt3...Crystal structure of the Escherichia coli peptide methionine sulphoxide reductase at 1.9 Å resolution . Struct. Fold. Des. 8: 1167 – 1178. 2 . Brot...sources (8). There is a 67% sequence identity between the E.coli and human MsrA ( 2 ). N-terminus C-terminus Figure 2 . Three-dimensional structure

Diffuse Interface Methods for Multiclass Segmentation of High-Dimensional Data

DTIC Science & Technology

2014-03-04

handwritten digits , 1998. http://yann.lecun.com/exdb/mnist/. [19] S. Nene, S. Nayar, H. Murase, Columbia Object Image Library (COIL-100), Technical Report... recognition on smartphones using a multiclass hardware-friendly support vector machine, in: Ambient Assisted Living and Home Care, Springer, 2012, pp. 216–223.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Three-dimensional printing: review of application in medicine and hepatic surgery.

PubMed

Yao, Rui; Xu, Gang; Mao, Shuang-Shuang; Yang, Hua-Yu; Sang, Xin-Ting; Sun, Wei; Mao, Yi-Lei

2016-12-01

Three-dimensional (3D) printing (3DP) is a rapid prototyping technology that has gained increasing recognition in many different fields. Inherent accuracy and low-cost property enable applicability of 3DP in many areas, such as manufacturing, aerospace, medical, and industrial design. Recently, 3DP has gained considerable attention in the medical field. The image data can be quickly turned into physical objects by using 3DP technology. These objects are being used across a variety of surgical specialties. The shortage of cadaver specimens is a major problem in medical education. However, this concern has been solved with the emergence of 3DP model. Custom-made items can be produced by using 3DP technology. This innovation allows 3DP use in preoperative planning and surgical training. Learning is difficult among medical students because of the complex anatomical structures of the liver. Thus, 3D visualization is a useful tool in anatomy teaching and hepatic surgical training. However, conventional models do not capture haptic qualities. 3DP can produce highly accurate and complex physical models. Many types of human or animal differentiated cells can be printed successfully with the development of 3D bio-printing technology. This progress represents a valuable breakthrough that exhibits many potential uses, such as research on drug metabolism or liver disease mechanism. This technology can also be used to solve shortage of organs for transplant in the future.

Three-dimensional printing: review of application in medicine and hepatic surgery

PubMed Central

Yao, Rui; Xu, Gang; Mao, Shuang-Shuang; Yang, Hua-Yu; Sang, Xin-Ting; Sun, Wei; Mao, Yi-Lei

2016-01-01

Three-dimensional (3D) printing (3DP) is a rapid prototyping technology that has gained increasing recognition in many different fields. Inherent accuracy and low-cost property enable applicability of 3DP in many areas, such as manufacturing, aerospace, medical, and industrial design. Recently, 3DP has gained considerable attention in the medical field. The image data can be quickly turned into physical objects by using 3DP technology. These objects are being used across a variety of surgical specialties. The shortage of cadaver specimens is a major problem in medical education. However, this concern has been solved with the emergence of 3DP model. Custom-made items can be produced by using 3DP technology. This innovation allows 3DP use in preoperative planning and surgical training. Learning is difficult among medical students because of the complex anatomical structures of the liver. Thus, 3D visualization is a useful tool in anatomy teaching and hepatic surgical training. However, conventional models do not capture haptic qualities. 3DP can produce highly accurate and complex physical models. Many types of human or animal differentiated cells can be printed successfully with the development of 3D bio-printing technology. This progress represents a valuable breakthrough that exhibits many potential uses, such as research on drug metabolism or liver disease mechanism. This technology can also be used to solve shortage of organs for transplant in the future. PMID:28154775

Analysis of objects in binary images. M.S. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Leonard, Desiree M.

1991-01-01

Digital image processing techniques are typically used to produce improved digital images through the application of successive enhancement techniques to a given image or to generate quantitative data about the objects within that image. In support of and to assist researchers in a wide range of disciplines, e.g., interferometry, heavy rain effects on aerodynamics, and structure recognition research, it is often desirable to count objects in an image and compute their geometric properties. Therefore, an image analysis application package, focusing on a subset of image analysis techniques used for object recognition in binary images, was developed. This report describes the techniques and algorithms utilized in three main phases of the application and are categorized as: image segmentation, object recognition, and quantitative analysis. Appendices provide supplemental formulas for the algorithms employed as well as examples and results from the various image segmentation techniques and the object recognition algorithm implemented.

Three-dimensional rendering of segmented object using matlab - biomed 2010.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2010-01-01

The three-dimensional rendering of microscopic objects is a difficult and challenging task that often requires specialized image processing techniques. Previous work has been described of a semi-automatic segmentation process of fluorescently stained neurons collected as a sequence of slice images with a confocal laser scanning microscope. Once properly segmented, each individual object can be rendered and studied as a three-dimensional virtual object. This paper describes the work associated with the design and development of Matlab files to create three-dimensional images from the segmented object data previously mentioned. Part of the motivation for this work is to integrate both the segmentation and rendering processes into one software application, providing a seamless transition from the segmentation tasks to the rendering and visualization tasks. Previously these tasks were accomplished on two different computer systems, windows and Linux. This transition basically limits the usefulness of the segmentation and rendering applications to those who have both computer systems readily available. The focus of this work is to create custom Matlab image processing algorithms for object rendering and visualization, and merge these capabilities to the Matlab files that were developed especially for the image segmentation task. The completed Matlab application will contain both the segmentation and rendering processes in a single graphical user interface, or GUI. This process for rendering three-dimensional images in Matlab requires that a sequence of two-dimensional binary images, representing a cross-sectional slice of the object, be reassembled in a 3D space, and covered with a surface. Additional segmented objects can be rendered in the same 3D space. The surface properties of each object can be varied by the user to aid in the study and analysis of the objects. This inter-active process becomes a powerful visual tool to study and understand microscopic objects.

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

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

Object recognition for autonomous robot utilizing distributed knowledge database

NASA Astrophysics Data System (ADS)

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

2003-10-01

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

Spatial versus Object Visualisation: The Case of Mathematical Understanding in Three-Dimensional Arrays of Cubes and Nets

ERIC Educational Resources Information Center

Pitta-Pantazi, Demetra; Christou, Constantinos

2010-01-01

This paper investigates the relations of students' spatial and object visualisation with their analytic, creative and practical abilities in three-dimensional geometry. Fifty-three 11-year-olds were tested using a Greek modified version of the Object-Spatial Imagery Questionnaire (OSIQ) (Blajenkova, Kozhevnikov, & Motes, 2006) and two…

Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

PubMed

Wolff, J Gerard

2014-01-01

The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

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

PubMed

Kuwabara, Megumi; Smith, Linda B

2016-07-01

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

A three-dimensional laser vibration measurement technology realized on five laser beam and its calibration

NASA Astrophysics Data System (ADS)

Li, Lu-Ke; Zhang, Shen-Feng

2018-03-01

Put forward a kind of three-dimensional vibration information technology of vibrating object by the mean of five laser beam of He-Ne laser, and with the help of three-way sensor, measure the three-dimensional laser vibration developed by above mentioned technology. The technology based on the Doppler principle of interference and signal demodulation technology, get the vibration information of the object, through the algorithm processing, extract the three-dimensional vibration information of space objects, and can achieve the function of angle calibration of five beam in the space, which avoid the effects of the mechanical installation error, greatly improve the accuracy of measurement. With the help of a & B K4527 contact three axis sensor, measure and calibrate three-dimensional laser vibrometer, which ensure the accuracy of the measurement data. Summarize the advantages and disadvantages of contact and non-contact sensor, and analysis the future development trends of the sensor industry.

Producing a Linear Laser System for 3d Modelimg of Small Objects

NASA Astrophysics Data System (ADS)

Amini, A. Sh.; Mozaffar, M. H.

2012-07-01

Today, three dimensional modeling of objects is considered in many applications such as documentation of ancient heritage, quality control, reverse engineering and animation In this regard, there are a variety of methods for producing three-dimensional models. In this paper, a 3D modeling system is developed based on photogrammetry method using image processing and laser line extraction from images. In this method the laser beam profile is radiated on the body of the object and with video image acquisition, and extraction of laser line from the frames, three-dimensional coordinates of the objects can be achieved. In this regard, first the design and implementation of hardware, including cameras and laser systems was conducted. Afterwards, the system was calibrated. Finally, the software of the system was implemented for three dimensional data extraction. The system was investigated for modeling a number of objects. The results showed that the system can provide benefits such as low cost, appropriate speed and acceptable accuracy in 3D modeling of objects.

A New Classification of Three-Dimensional Printing Technologies: Systematic Review of Three-Dimensional Printing for Patient-Specific Craniomaxillofacial Surgery.

PubMed

Jacobs, Carly A; Lin, Alexander Y

2017-05-01

Three-dimensional printing technology has been advancing in surgical applications. This systematic review examines its patient-specific applications in craniomaxillofacial surgery. Terms related to "three-dimensional printing" and "surgery" were searched on PubMed on May 4, 2015; 313 unique articles were returned. Inclusion and exclusion criteria concentrated on patient-specific surgical applications, yielding 141 full-text articles, of which 33 craniomaxillofacial articles were analyzed. Thirty-three articles included 315 patients who underwent three-dimensional printing-assisted operations. The most common modeling software was Mimics, the most common printing software was 3D Systems, the average time to create a printed object was 18.9 hours (range, 1.5 to 96 hours), and the average cost of a printed object was $1353.31 (range, $69.75 to $5500). Surgical procedures were divided among 203 craniofacial patients (205 three-dimensional printing objects) and 112 maxillofacial patients (137 objects). Printing technologies could be classified as contour models, guides, splints, and implants. For craniofacial patients, 173 contour models (84 percent), 13 guides (6 percent), two splints (1 percent), and 17 implants (8 percent) were made. For maxillofacial patients, 41 contour models (30 percent), 48 guides (35 percent), 40 splints (29 percent), and eight implants (6 percent) were made. These distributions were significantly different (p < 0.0001). Four studies compared three-dimensional printing techniques to conventional techniques; two of them found that three-dimensional printing produced improved outcomes. Three-dimensional printing technology in craniomaxillofacial surgery can be classified into contour models (type I), guides (type II), splints (type III), and implants (type IV). These four methods vary in their use between craniofacial and maxillofacial surgery, reflecting their different goals. This understanding may help advance and predict three-dimensional printing applications for other types of plastic surgery and beyond.

Semantic and visual determinants of face recognition in a prosopagnosic patient.

PubMed

Dixon, M J; Bub, D N; Arguin, M

1998-05-01

Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

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

ERIC Educational Resources Information Center

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

2013-01-01

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

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

ERIC Educational Resources Information Center

Pereira, Alfredo F.; Smith, Linda B.

2009-01-01

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

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

PubMed

Smith, Linda B

2013-11-01

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

An expanded framework for biomolecular visualization in the classroom: Learning goals and competencies.

PubMed

Dries, Daniel R; Dean, Diane M; Listenberger, Laura L; Novak, Walter R P; Franzen, Margaret A; Craig, Paul A

2017-01-02

A thorough understanding of the molecular biosciences requires the ability to visualize and manipulate molecules in order to interpret results or to generate hypotheses. While many instructors in biochemistry and molecular biology use visual representations, few indicate that they explicitly teach visual literacy. One reason is the need for a list of core content and competencies to guide a more deliberate instruction in visual literacy. We offer here the second stage in the development of one such resource for biomolecular three-dimensional visual literacy. We present this work with the goal of building a community for online resource development and use. In the first stage, overarching themes were identified and submitted to the biosciences community for comment: atomic geometry; alternate renderings; construction/annotation; het group recognition; molecular dynamics; molecular interactions; monomer recognition; symmetry/asymmetry recognition; structure-function relationships; structural model skepticism; and topology and connectivity. Herein, the overarching themes have been expanded to include a 12th theme (macromolecular assemblies), 27 learning goals, and more than 200 corresponding objectives, many of which cut across multiple overarching themes. The learning goals and objectives offered here provide educators with a framework on which to map the use of molecular visualization in their classrooms. In addition, the framework may also be used by biochemistry and molecular biology educators to identify gaps in coverage and drive the creation of new activities to improve visual literacy. This work represents the first attempt, to our knowledge, to catalog a comprehensive list of explicit learning goals and objectives in visual literacy. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):69-75, 2017. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology.

Real three-dimensional objects: effects on mental rotation.

PubMed

Felix, Michael C; Parker, Joshua D; Lee, Charles; Gabriel, Kara I

2011-08-01

The current experiment investigated real three-dimensional (3D) objects with regard to performance on a mental rotation task and whether the appearance of sex differences may be mediated by experiences with spatially related activities. 40 men and 40 women were presented with alternating timed trials consisting of real-3D objects or two-dimensional illustrations of 3D objects. Sex differences in spatially related activities did not significantly influence the finding that men outperformed women on mental rotation of either stimulus type. However, on measures related to spatial activities, self-reported proficiency using maps correlated positively with performance only on trials with illustrations whereas self-reported proficiency using GPS correlated negatively with performance regardless of stimulus dimensionality. Findings may be interpreted as suggesting that rotating real-3D objects utilizes distinct but overlapping spatial skills compared to rotating two-dimensional representations of 3D objects, and real-3D objects can enhance mental rotation performance.

Localized contourlet features in vehicle make and model recognition

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

Two- vs. Three-Dimensional Presentation of Mental Rotation Tasks: Sex Differences and Effects of Training on Performance and Brain Activation

ERIC Educational Resources Information Center

Neubauer, Aljoscha C.; Bergner, Sabine; Schatz, Martina

2010-01-01

The well-documented sex difference in mental rotation favoring males has been shown to emerge only for 2-dimensional presentations of 3-dimensional objects, but not with actual 3-dimensional objects or with virtual reality presentations of 3-dimensional objects. Training studies using computer games with mental rotation-related content have…

Object-based spatial attention when objects have sufficient depth cues.

PubMed

Takeya, Ryuji; Kasai, Tetsuko

2015-01-01

Attention directed to a part of an object tends to obligatorily spread over all of the spatial regions that belong to the object, which may be critical for rapid object-recognition in cluttered visual scenes. Previous studies have generally used simple rectangles as objects and have shown that attention spreading is reflected by amplitude modulation in the posterior N1 component (150-200 ms poststimulus) of event-related potentials, while other interpretations (i.e., rectangular holes) may arise implicitly in early visual processing stages. By using modified Kanizsa-type stimuli that provided less ambiguity of depth ordering, the present study examined early event-related potential spatial-attention effects for connected and separated objects, both of which were perceived in front of (Experiment 1) and in back of (Experiment 2) the surroundings. Typical P1 (100-140 ms) and N1 (150-220 ms) attention effects of ERP in response to unilateral probes were observed in both experiments. Importantly, the P1 attention effect was decreased for connected objects compared to separated objects only in Experiment 1, and the typical object-based modulations of N1 were not observed in either experiment. These results suggest that spatial attention spreads over a figural object at earlier stages of processing than previously indicated, in three-dimensional visual scenes with multiple depth cues.

Nondestructive analysis of three-dimensional objects using a fluid displacement method

USDA-ARS?s Scientific Manuscript database

Quantification of three-dimensional (3-D) objects has been a real challenge in agricultural, hydrological and environmental studies. We designed and tested a method that is capable of quantifying 3-D objects using measurements of fluid displacement. The device consists of a stand that supports a mov...

Paradigm shift regarding the transversalis fascia, preperitoneal space, and Retzius' space.

PubMed

Asakage, N

2018-06-01

There has been confusion in the anatomical recognition when performing inguinal hernia operations in Japan. From now on, a paradigm shift from the concept of two-dimensional layer structure to the three-dimensional space recognition is necessary to promote an understanding of anatomy. Along with the formation of the abdominal wall, the extraperitoneal space is formed by the transversalis fascia and preperitoneal space. The transversalis fascia is a somatic vascular fascia originating from an arteriovenous fascia. It is a dense areolar tissue layer at the outermost of the extraperitoneal space that runs under the diaphragm and widely lines the body wall muscle. The umbilical funiculus is taken into the abdominal wall and transformed into the preperitoneal space that is a local three-dimensional cavity enveloping preperitoneal fasciae composed of the renal fascia, vesicohypogastric fascia, and testiculoeferential fascia. The Retzius' space is an artificial cavity formed at the boundary between the transversalis fascia and preperitoneal space. In the underlay mesh repair, the mesh expands in the range spanning across the Retzius' space and preperitoneal space.

Deep neural network using color and synthesized three-dimensional shape for face recognition

NASA Astrophysics Data System (ADS)

Rhee, Seon-Min; Yoo, ByungIn; Han, Jae-Joon; Hwang, Wonjun

2017-03-01

We present an approach for face recognition using synthesized three-dimensional (3-D) shape information together with two-dimensional (2-D) color in a deep convolutional neural network (DCNN). As 3-D facial shape is hardly affected by the extrinsic 2-D texture changes caused by illumination, make-up, and occlusions, it could provide more reliable complementary features in harmony with the 2-D color feature in face recognition. Unlike other approaches that use 3-D shape information with the help of an additional depth sensor, our approach generates a personalized 3-D face model by using only face landmarks in the 2-D input image. Using the personalized 3-D face model, we generate a frontalized 2-D color facial image as well as 3-D facial images (e.g., a depth image and a normal image). In our DCNN, we first feed 2-D and 3-D facial images into independent convolutional layers, where the low-level kernels are successfully learned according to their own characteristics. Then, we merge them and feed into higher-level layers under a single deep neural network. Our proposed approach is evaluated with labeled faces in the wild dataset and the results show that the error rate of the verification rate at false acceptance rate 1% is improved by up to 32.1% compared with the baseline where only a 2-D color image is used.

Interface of Augmented Reality Game Using Face Tracking and Its Application to Advertising

NASA Astrophysics Data System (ADS)

Lee, Young Jae; Lee, Yong Jae

This paper proposes the face interface method which can be used in recognizing gamer's movements in the real world for application in the cyber space so that we could make three-dimensional space recognition motion-based game. The proposed algorithm is the new face recognition technology which incorporates the strengths of two existing algorithms, CBCH and CAMSHIFT and its validity has been proved through a series of experiments. Moreover, for the purpose of the interdisciplinary studies, concepts of advertising have been introduced into the three-dimensional motion-based game to look into the possible new beneficiary models for the game industry. This kind of attempt may be significant in that it tried to see if the advertising brand when placed in the game could play the role of the game item or quest. The proposed method can provide the basic references for developing motion-based game development.

Two-dimensional shape recognition using oriented-polar representation

NASA Astrophysics Data System (ADS)

Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li

1997-10-01

To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.

Is the digitization of laparoscopic movement using accessible alternative technologies possible?

PubMed

Lorias Espinoza, Daniel; Gutiérrez Gnecchi, José Antonio; Martínez, Arturo Minor

2012-05-01

It is widely documented that laparoscopic surgeons require training, and an objective evaluation of the training that they receive. The most advanced evaluation systems integrate the digitization of the movement of laparoscopic tools. A great number of these systems, however, do not permit the use of real tools and their high cost limits their academic impact. Likewise, it is documented that new and accessible systems need to be developed. The aim of this article is to explore the possibility of digitizing the movement of laparoscopic tools in a three-dimensional workspace, using accessible alternative technology. Our proposal uses a commercial Wii video game control in conjunction with a program for determining kinematic variables during the execution of a recognition task.

SVM based colon polyps classifier in a wireless active stereo endoscope.

PubMed

Ayoub, J; Granado, B; Mhanna, Y; Romain, O

2010-01-01

This work focuses on the recognition of three-dimensional colon polyps captured by an active stereo vision sensor. The detection algorithm consists of SVM classifier trained on robust feature descriptors. The study is related to Cyclope, this prototype sensor allows real time 3D object reconstruction and continues to be optimized technically to improve its classification task by differentiation between hyperplastic and adenomatous polyps. Experimental results were encouraging and show correct classification rate of approximately 97%. The work contains detailed statistics about the detection rate and the computing complexity. Inspired by intensity histogram, the work shows a new approach that extracts a set of features based on depth histogram and combines stereo measurement with SVM classifiers to correctly classify benign and malignant polyps.

Automatic anatomy recognition in whole-body PET/CT images

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

Wang, Huiqian; Udupa, Jayaram K., E-mail: jay@mail.med.upenn.edu; Odhner, Dewey

Purpose: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity ofmore » anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process, to bring performance to the level achieved on diagnostic CT and MR images in body-region-wise approaches. The intermodality approach fosters the use of already existing fuzzy models, previously created from diagnostic CT images, on PET/CT and other derived images, thus truly separating the modality-independent object assembly anatomy from modality-specific tissue property portrayal in the image. Results: Key ways of combining the above three basic ideas lead them to 15 different strategies for recognizing objects in PET/CT images. Utilizing 50 diagnostic CT image data sets from the thoracic and abdominal body regions and 16 whole-body PET/CT image data sets, the authors compare the recognition performance among these 15 strategies on 18 objects from the thorax, abdomen, and pelvis in object localization error and size estimation error. Particularly on texture membership images, object localization is within three voxels on whole-body low-dose CT images and 2 voxels on body-region-wise low-dose images of known true locations. Surprisingly, even on direct body-region-wise PET images, localization error within 3 voxels seems possible. Conclusions: The previous body-region-wise approach can be extended to whole-body torso with similar object localization performance. Combined use of image texture and intensity property yields the best object localization accuracy. In both body-region-wise and whole-body approaches, recognition performance on low-dose CT images reaches levels previously achieved on diagnostic CT images. The best object recognition strategy varies among objects; the proposed framework however allows employing a strategy that is optimal for each object.« less

Aging and solid shape recognition: Vision and haptics.

PubMed

Norman, J Farley; Cheeseman, Jacob R; Adkins, Olivia C; Cox, Andrea G; Rogers, Connor E; Dowell, Catherine J; Baxter, Michael W; Norman, Hideko F; Reyes, Cecia M

2015-10-01

The ability of 114 younger and older adults to recognize naturally-shaped objects was evaluated in three experiments. The participants viewed or haptically explored six randomly-chosen bell peppers (Capsicum annuum) in a study session and were later required to judge whether each of twelve bell peppers was "old" (previously presented during the study session) or "new" (not presented during the study session). When recognition memory was tested immediately after study, the younger adults' (Experiment 1) performance for vision and haptics was identical when the individual study objects were presented once. Vision became superior to haptics, however, when the individual study objects were presented multiple times. When 10- and 20-min delays (Experiment 2) were inserted in between study and test sessions, no significant differences occurred between vision and haptics: recognition performance in both modalities was comparable. When the recognition performance of older adults was evaluated (Experiment 3), a negative effect of age was found for visual shape recognition (younger adults' overall recognition performance was 60% higher). There was no age effect, however, for haptic shape recognition. The results of the present experiments indicate that the visual recognition of natural object shape is different from haptic recognition in multiple ways: visual shape recognition can be superior to that of haptics and is affected by aging, while haptic shape recognition is less accurate and unaffected by aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Sundstrøm, Martin

2011-07-01

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

[Application of rational ant colony optimization to improve the reproducibility degree of laser three-dimensional copy].

PubMed

Cui, Xiao-Yan; Huo, Zhong-Gang; Xin, Zhong-Hua; Tian, Xiao; Zhang, Xiao-Dong

2013-07-01

Three-dimensional (3D) copying of artificial ears and pistol printing are pushing laser three-dimensional copying technique to a new page. Laser three-dimensional scanning is a fresh field in laser application, and plays an irreplaceable part in three-dimensional copying. Its accuracy is the highest among all present copying techniques. Reproducibility degree marks the agreement of copied object with the original object on geometry, being the most important index property in laser three-dimensional copying technique. In the present paper, the error of laser three-dimensional copying was analyzed. The conclusion is that the data processing to the point cloud of laser scanning is the key technique to reduce the error and increase the reproducibility degree. The main innovation of this paper is as follows. On the basis of traditional ant colony optimization, rational ant colony optimization algorithm proposed by the author was applied to the laser three-dimensional copying as a new algorithm, and was put into practice. Compared with customary algorithm, rational ant colony optimization algorithm shows distinct advantages in data processing of laser three-dimensional copying, reducing the error and increasing the reproducibility degree of the copy.

System and method for representing and manipulating three-dimensional objects on massively parallel architectures

DOEpatents

Karasick, M.S.; Strip, D.R.

1996-01-30

A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modeling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modeling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modeling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication. 8 figs.

Young Infants' Perception of the Trajectories of Two- and Three-Dimensional Objects

ERIC Educational Resources Information Center

Johnson, Scott P.; Bremner, J. Gavin; Slater, Alan M.; Shuwairi, Sarah M.; Mason, Uschi; Spring, Jo; Usherwood, Barrie

2012-01-01

We investigated oculomotor anticipations in 4-month-old infants as they viewed center-occluded object trajectories. In two experiments, we examined performance in two-dimensional (2D) and three-dimensional (3D) dynamic occlusion displays and in an additional 3D condition with a smiley face as the moving target stimulus. Rates of anticipatory eye…

Scattering calculation and image reconstruction using elevation-focused beams

PubMed Central

Duncan, David P.; Astheimer, Jeffrey P.; Waag, Robert C.

2009-01-01

Pressure scattered by cylindrical and spherical objects with elevation-focused illumination and reception has been analytically calculated, and corresponding cross sections have been reconstructed with a two-dimensional algorithm. Elevation focusing was used to elucidate constraints on quantitative imaging of three-dimensional objects with two-dimensional algorithms. Focused illumination and reception are represented by angular spectra of plane waves that were efficiently computed using a Fourier interpolation method to maintain the same angles for all temporal frequencies. Reconstructions were formed using an eigenfunction method with multiple frequencies, phase compensation, and iteration. The results show that the scattered pressure reduces to a two-dimensional expression, and two-dimensional algorithms are applicable when the region of a three-dimensional object within an elevation-focused beam is approximately constant in elevation. The results also show that energy scattered out of the reception aperture by objects contained within the focused beam can result in the reconstructed values of attenuation slope being greater than true values at the boundary of the object. Reconstructed sound speed images, however, appear to be relatively unaffected by the loss in scattered energy. The broad conclusion that can be drawn from these results is that two-dimensional reconstructions require compensation to account for uncaptured three-dimensional scattering. PMID:19425653

Scattering calculation and image reconstruction using elevation-focused beams.

PubMed

Duncan, David P; Astheimer, Jeffrey P; Waag, Robert C

2009-05-01

Pressure scattered by cylindrical and spherical objects with elevation-focused illumination and reception has been analytically calculated, and corresponding cross sections have been reconstructed with a two-dimensional algorithm. Elevation focusing was used to elucidate constraints on quantitative imaging of three-dimensional objects with two-dimensional algorithms. Focused illumination and reception are represented by angular spectra of plane waves that were efficiently computed using a Fourier interpolation method to maintain the same angles for all temporal frequencies. Reconstructions were formed using an eigenfunction method with multiple frequencies, phase compensation, and iteration. The results show that the scattered pressure reduces to a two-dimensional expression, and two-dimensional algorithms are applicable when the region of a three-dimensional object within an elevation-focused beam is approximately constant in elevation. The results also show that energy scattered out of the reception aperture by objects contained within the focused beam can result in the reconstructed values of attenuation slope being greater than true values at the boundary of the object. Reconstructed sound speed images, however, appear to be relatively unaffected by the loss in scattered energy. The broad conclusion that can be drawn from these results is that two-dimensional reconstructions require compensation to account for uncaptured three-dimensional scattering.

Ligation site in proteins recognized in silico

PubMed Central

Brylinski, Michal; Konieczny, Leszek; Roterman, Irena

2006-01-01

Recognition of a ligation site in a protein molecule is important for identifying its biological activity. The model for in silico recognition of ligation sites in proteins is presented. The idealized hydrophobic core stabilizing protein structure is represented by a three-dimensional Gaussian function. The experimentally observed distribution of hydrophobicity compared with the theoretical distribution reveals differences. The area of high differences indicates the ligation site. Availability http://bioinformatics.cm-uj.krakow.pl/activesite PMID:17597871

Computer-Generated, Three-Dimensional Character Animation.

ERIC Educational Resources Information Center

Van Baerle, Susan Lynn

This master's thesis begins by discussing the differences between 3-D computer animation of solid three-dimensional, or monolithic, objects, and the animation of characters, i.e., collections of movable parts with soft pliable surfaces. Principles from two-dimensional character animation that can be transferred to three-dimensional character…

Three-dimensional surface reconstruction for industrial computed tomography

NASA Technical Reports Server (NTRS)

Vannier, M. W.; Knapp, R. H.; Gayou, D. E.; Sammon, N. P.; Butterfield, R. L.; Larson, J. W.

1985-01-01

Modern high resolution medical computed tomography (CT) scanners can produce geometrically accurate sectional images of many types of industrial objects. Computer software has been developed to convert serial CT scans into a three-dimensional surface form, suitable for display on the scanner itself. This software, originally developed for imaging the skull, has been adapted for application to industrial CT scanning, where serial CT scans thrrough an object of interest may be reconstructed to demonstrate spatial relationships in three dimensions that cannot be easily understood using the original slices. The methods of three-dimensional reconstruction and solid modeling are reviewed, and reconstruction in three dimensions from CT scans through familiar objects is demonstrated.

Subpixel based defocused points removal in photon-limited volumetric dataset

NASA Astrophysics Data System (ADS)

Muniraj, Inbarasan; Guo, Changliang; Malallah, Ra'ed; Maraka, Harsha Vardhan R.; Ryle, James P.; Sheridan, John T.

2017-03-01

The asymptotic property of the maximum likelihood estimator (MLE) has been utilized to reconstruct three-dimensional (3D) sectional images in the photon counting imaging (PCI) regime. At first, multiple 2D intensity images, known as Elemental images (EI), are captured. Then the geometric ray-tracing method is employed to reconstruct the 3D sectional images at various depth cues. We note that a 3D sectional image consists of both focused and defocused regions, depending on the reconstructed depth position. The defocused portion is redundant and should be removed in order to facilitate image analysis e.g., 3D object tracking, recognition, classification and navigation. In this paper, we present a subpixel level three-step based technique (i.e. involving adaptive thresholding, boundary detection and entropy based segmentation) to discard the defocused sparse-samples from the reconstructed photon-limited 3D sectional images. Simulation results are presented demonstrating the feasibility and efficiency of the proposed method.

[Extraction and recognition of attractors in three-dimensional Lorenz plot].

PubMed

Hu, Min; Jang, Chengfan; Wang, Suxia

2018-02-01

Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X , Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency ( A PF ) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, A PF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.

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.

Acoustic basis for recognition of aspect-dependent three-dimensional targets by an echolocating bottlenose dolphin.

PubMed

Helweg, D A; Au, W W; Roitblat, H L; Nachtigall, P E

1996-04-01

The relationships between acoustic features of target echoes and the cognitive representations of the target formed by an echolocating dolphin will influence the ease with which the dolphin can recognize a target. A blindfolded Atlantic bottlenose dolphin (Tursiops truncatus) learned to match aspect-dependent three-dimensional targets (such as a cube) at haphazard orientations, although with some difficulty. This task may have been difficult because aspect-dependent targets produce different echoes at different orientations, which required the dolphin to have some capability for object constancy across changes in echo characteristics. Significant target-related differences in echo amplitude, rms bandwidth, and distributions of interhighlight intervals were observed among echoes collected when the dolphin was performing the task. Targets could be classified using a combination of energy flux density and rms bandwidth by a linear discriminant analysis and a nearest centroid classifier. Neither statistical model could classify targets without amplitude information, but the highest accuracy required spectral information as well. This suggests that the dolphin recognized the targets using a multidimensional representation containing amplitude and spectral information and that dolphins can form stable representations of targets regardless of orientation based on varying sensory properties.

Diffraction mode terahertz tomography

DOEpatents

Ferguson, Bradley; Wang, Shaohong; Zhang, Xi-Cheng

2006-10-31

A method of obtaining a series of images of a three-dimensional object. The method includes the steps of transmitting pulsed terahertz (THz) radiation through the entire object from a plurality of angles, optically detecting changes in the transmitted THz radiation using pulsed laser radiation, and constructing a plurality of imaged slices of the three-dimensional object using the detected changes in the transmitted THz radiation. The THz radiation is transmitted through the object as a two-dimensional array of parallel rays. The optical detection is an array of detectors such as a CCD sensor.

Image formation of thick three-dimensional objects in differential-interference-contrast microscopy.

PubMed

Trattner, Sigal; Kashdan, Eugene; Feigin, Micha; Sochen, Nir

2014-05-01

The differential-interference-contrast (DIC) microscope is of widespread use in life sciences as it enables noninvasive visualization of transparent objects. The goal of this work is to model the image formation process of thick three-dimensional objects in DIC microscopy. The model is based on the principles of electromagnetic wave propagation and scattering. It simulates light propagation through the components of the DIC microscope to the image plane using a combined geometrical and physical optics approach and replicates the DIC image of the illuminated object. The model is evaluated by comparing simulated images of three-dimensional spherical objects with the recorded images of polystyrene microspheres. Our computer simulations confirm that the model captures the major DIC image characteristics of the simulated object, and it is sensitive to the defocusing effects.

Involvement of hippocampal NMDA receptors in encoding and consolidation, but not retrieval, processes of spontaneous object location memory in rats.

PubMed

Yamada, Kazuo; Arai, Misaki; Suenaga, Toshiko; Ichitani, Yukio

2017-07-28

The hippocampus is thought to be involved in object location recognition memory, yet the contribution of hippocampal NMDA receptors to the memory processes, such as encoding, retention and retrieval, is unknown. First, we confirmed that hippocampal infusion of a competitive NMDA receptor antagonist, AP5 (2-amino-5-phosphonopentanoic acid, 20-40nmol), impaired performance of spontaneous object location recognition test but not that of novel object recognition test in Wistar rats. Next, the effects of hippocampal AP5 treatment on each process of object location recognition memory were examined with three different injection times using a 120min delay-interposed test: 15min before the sample phase (Time I), immediately after the sample phase (Time II), and 15min before the test phase (Time III). The blockade of hippocampal NMDA receptors before and immediately after the sample phase, but not before the test phase, markedly impaired performance of object location recognition test, suggesting that hippocampal NMDA receptors play an important role in encoding and consolidation/retention, but not retrieval, of spontaneous object location memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Face recognition by applying wavelet subband representation and kernel associative memory.

PubMed

Zhang, Bai-Ling; Zhang, Haihong; Ge, Shuzhi Sam

2004-01-01

In this paper, we propose an efficient face recognition scheme which has two features: 1) representation of face images by two-dimensional (2-D) wavelet subband coefficients and 2) recognition by a modular, personalised classification method based on kernel associative memory models. Compared to PCA projections and low resolution "thumb-nail" image representations, wavelet subband coefficients can efficiently capture substantial facial features while keeping computational complexity low. As there are usually very limited samples, we constructed an associative memory (AM) model for each person and proposed to improve the performance of AM models by kernel methods. Specifically, we first applied kernel transforms to each possible training pair of faces sample and then mapped the high-dimensional feature space back to input space. Our scheme using modular autoassociative memory for face recognition is inspired by the same motivation as using autoencoders for optical character recognition (OCR), for which the advantages has been proven. By associative memory, all the prototypical faces of one particular person are used to reconstruct themselves and the reconstruction error for a probe face image is used to decide if the probe face is from the corresponding person. We carried out extensive experiments on three standard face recognition datasets, the FERET data, the XM2VTS data, and the ORL data. Detailed comparisons with earlier published results are provided and our proposed scheme offers better recognition accuracy on all of the face datasets.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Fast and efficient indexing approach for object recognition

NASA Astrophysics Data System (ADS)

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

1999-08-01

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

Exploring the CAESAR database using dimensionality reduction techniques

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Raymer, Michael L.

2012-06-01

The Civilian American and European Surface Anthropometry Resource (CAESAR) database containing over 40 anthropometric measurements on over 4000 humans has been extensively explored for pattern recognition and classification purposes using the raw, original data [1-4]. However, some of the anthropometric variables would be impossible to collect in an uncontrolled environment. Here, we explore the use of dimensionality reduction methods in concert with a variety of classification algorithms for gender classification using only those variables that are readily observable in an uncontrolled environment. Several dimensionality reduction techniques are employed to learn the underlining structure of the data. These techniques include linear projections such as the classical Principal Components Analysis (PCA) and non-linear (manifold learning) techniques, such as Diffusion Maps and the Isomap technique. This paper briefly describes all three techniques, and compares three different classifiers, Naïve Bayes, Adaboost, and Support Vector Machines (SVM), for gender classification in conjunction with each of these three dimensionality reduction approaches.

Ageing affects event-related potentials and brain oscillations: a behavioral and electrophysiological study using a haptic recognition memory task.

PubMed

Sebastián, Manuel; Reales, José M; Ballesteros, Soledad

2011-12-01

In this electrophysiological study, we investigated the effects of ageing on recognition memory for three-dimensional (3D) familiar objects presented to touch in a continuous paradigm. To examine changes in event-related potentials (ERPs) and brain oscillations, we recorded the EEGs of healthy groups of young (n=14; mean age=32.3 years) and older adults (n=14; mean age=65.1). Both age groups exhibited similar accuracy and exploration times when making old-new judgments. Young and older participants showed a marginally significant ERP old/new effect widely distributed over the scalp between 550-750 ms. In addition, the elders showed lower amplitude than younger participants within 1200-1500 ms. There were age-related differences in brain oscillations as measured by event-related spectral perturbation (ERSP). Older adults showed greater alpha and beta power reductions than young participants, suggesting the recruitment of additional neural resources. In contrast, the two age groups showed a reliable old/new effect in the theta band that temporarily overlapped the ERP old/new effect. The present results suggest that despite similar behavioral performance, the young and older adults recruited different neural resources to perform a haptic recognition task. Copyright © 2011 Elsevier Ltd. All rights reserved.

Appearance-based representative samples refining method for palmprint recognition

NASA Astrophysics Data System (ADS)

Wen, Jiajun; Chen, Yan

2012-07-01

The sparse representation can deal with the lack of sample problem due to utilizing of all the training samples. However, the discrimination ability will degrade when more training samples are used for representation. We propose a novel appearance-based palmprint recognition method. We aim to find a compromise between the discrimination ability and the lack of sample problem so as to obtain a proper representation scheme. Under the assumption that the test sample can be well represented by a linear combination of a certain number of training samples, we first select the representative training samples according to the contributions of the samples. Then we further refine the training samples by an iteration procedure, excluding the training sample with the least contribution to the test sample for each time. Experiments on PolyU multispectral palmprint database and two-dimensional and three-dimensional palmprint database show that the proposed method outperforms the conventional appearance-based palmprint recognition methods. Moreover, we also explore and find out the principle of the usage for the key parameters in the proposed algorithm, which facilitates to obtain high-recognition accuracy.

Supervised linear dimensionality reduction with robust margins for object recognition

NASA Astrophysics Data System (ADS)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Reading K-3. Instructional Objectives Exchange. A Project of the Center for the Study of Evaluation.

ERIC Educational Resources Information Center

California Univ., Los Angeles. Center for the Study of Evaluation.

Three hundred and ninety-seven objectives and related evaluation items for reading in grades kindergarten through three are presented for the teacher and administrator in this collection developed by the Instructional Objectives Exchange (IOX). The objectives are organized into the categories of word recognition, comprehension, and study skills,…

System for forming a quadrified image comprising angularly related fields of view of a three dimensional object

NASA Technical Reports Server (NTRS)

Chamberlain, F. R. (Inventor)

1980-01-01

A system for generating, within a single frame of photographic film, a quadrified image including images of angularly (including orthogonally) related fields of view of a near field three dimensional object is described. It is characterized by three subsystems each of which includes a plurality of reflective surfaces for imaging a different field of view of the object at a different quadrant of the quadrified image. All of the subsystems have identical path lengths to the object photographed.

The apparent size of three-dimensional objects and their silhouettes: a solid-superiority effect.

PubMed

Walker, J T; Walker, M J

1988-01-01

A solid object looks larger than its outline or silhouette under many viewing conditions. This solid-superiority effect may result from the assimilation or confusion of visual contours within the projection of a three-dimensional object on the picture plane. An aspect of the Müller-Lyer illusion may also play a role.

Building Bridges to Spatial Reasoning

ERIC Educational Resources Information Center

Shumway, Jessica F.

2013-01-01

Spatial reasoning, which involves "building and manipulating mental representations of two-and three-dimensional objects and perceiving an object from different perspectives" is a critical aspect of geometric thinking and reasoning. Through building, drawing, and analyzing two-and three-dimensional shapes, students develop a foundation…

High-performance mushroom plasmonic metamaterial absorbers for infrared polarimetric imaging

NASA Astrophysics Data System (ADS)

Ogawa, Shinpei; Fujisawa, Daisuke; Hata, Hisatoshi; Uetsuki, Mitsuharu; Kuboyama, Takafumi; Kimata, Masafumi

2017-02-01

Infrared (IR) polarimetric imaging is a promising approach to enhance object recognition with conventional IR imaging for applications such as artificial object recognition from the natural environment and facial recognition. However, typical infrared polarimetric imaging requires the attachment of polarizers to an IR camera or sensor, which leads to high cost and lower performance caused by their own IR radiation. We have developed asymmetric mushroom plasmonic metamaterial absorbers (A-MPMAs) to address this challenge. The A-MPMAs have an all-Al construction that consists of micropatches and a reflector layer connected with hollow rectangular posts. The asymmetric-shaped micropatches lead to strong polarization-selective IR absorption due to localized surface plasmon resonance at the micropatches. The operating wavelength region can be controlled mainly by the micropatch and the hollow rectangular post size. AMPMAs are complicated three-dimensional structures, the fabrication of which is challenging. Hollow rectangular post structures are introduced to enable simple fabrication using conventional surface micromachining techniques, such as sacrificial layer etching, with no degradation of the optical properties. The A-MPMAs have a smaller thermal mass than metal-insulator-metal based metamaterials and no influence of the strong non-linear dispersion relation of the insulator materials constant, which produces a gap in the wavelength region and additional absorption insensitive to polarization. A-MPMAs are therefore promising candidates for uncooled IR polarimetric image sensors in terms of both their optical properties and ease of fabrication. The results presented here are expected to contribute to the development of highperformance polarimetric uncooled IR image sensors that do not require polarizers.

Discriminating Power of Localized Three-Dimensional Facial Morphology

PubMed Central

Hammond, Peter; Hutton, Tim J.; Allanson, Judith E.; Buxton, Bernard; Campbell, Linda E.; Clayton-Smith, Jill; Donnai, Dian; Karmiloff-Smith, Annette; Metcalfe, Kay; Murphy, Kieran C.; Patton, Michael; Pober, Barbara; Prescott, Katrina; Scambler, Pete; Shaw, Adam; Smith, Ann C. M.; Stevens, Angela F.; Temple, I. Karen; Hennekam, Raoul; Tassabehji, May

2005-01-01

Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties. PMID:16380911

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

PubMed

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

2013-11-01

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

[Multi-Target Recognition of Internal and External Defects of Potato by Semi-Transmission Hyperspectral Imaging and Manifold Learning Algorithm].

PubMed

Huang, Tao; Li, Xiao-yu; Jin, Rui; Ku, Jing; Xu, Sen-miao; Xu, Meng-ling; Wu, Zhen-zhong; Kong, De-guo

2015-04-01

The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.

Identification and detection of simple 3D objects with severely blurred vision.

PubMed

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

2012-12-05

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. 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). 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%). 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.

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

PubMed

Tran, Dominic M D; Westbrook, R Frederick

2018-05-31

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

A DFT-Based Method of Feature Extraction for Palmprint Recognition

NASA Astrophysics Data System (ADS)

Choge, H. Kipsang; Karungaru, Stephen G.; Tsuge, Satoru; Fukumi, Minoru

Over the last quarter century, research in biometric systems has developed at a breathtaking pace and what started with the focus on the fingerprint has now expanded to include face, voice, iris, and behavioral characteristics such as gait. Palmprint is one of the most recent additions, and is currently the subject of great research interest due to its inherent uniqueness, stability, user-friendliness and ease of acquisition. This paper describes an effective and procedurally simple method of palmprint feature extraction specifically for palmprint recognition, although verification experiments are also conducted. This method takes advantage of the correspondences that exist between prominent palmprint features or objects in the spatial domain with those in the frequency or Fourier domain. Multi-dimensional feature vectors are formed by extracting a GA-optimized set of points from the 2-D Fourier spectrum of the palmprint images. The feature vectors are then used for palmprint recognition, before and after dimensionality reduction via the Karhunen-Loeve Transform (KLT). Experiments performed using palmprint images from the ‘PolyU Palmprint Database’ indicate that using a compact set of DFT coefficients, combined with KLT and data preprocessing, produces a recognition accuracy of more than 98% and can provide a fast and effective technique for personal identification.

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

PubMed

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

2018-07-01

Animals have the ability to process information about an object or a conspecific's physical features and location, and alter its behavior when such information is updated. In the laboratory, the object, spatial and social recognition are often studied in separate tasks, making them unsuitable to study the potential dissociations and interactions among various types of recognition memories. The present study introduced a single paradigm to detect the object and spatial recognition, and social recognition of a familiar and novel conspecific. Specifically, male and female Sprague-Dawley adult (>75 days old) or preadolescent (25-28 days old) rats were tested with two objects and one social partner in an open-field arena for four 10-min sessions with a 20-min inter-session interval. After the first sample session, a new object replaced one of the sampled objects in the second session, and the location of one of the old objects was changed in the third session. Finally, a new social partner was introduced in the fourth session and replaced the familiar one. Exploration time with each stimulus was recorded and measures for the three recognitions were calculated based on the discrimination ratio. Overall results show that adult and preadolescent male and female rats spent more time exploring the social partner than the objects, showing a clear preference for social stimulus over nonsocial one. They also did not differ in their abilities to discriminate a new object, a new location and a new social partner from a familiar one, and to recognize a familiar conspecific. Acute administration of MK-801 (a NMDA receptor antagonist, 0.025 and 0.10 mg/kg, i.p.) after the sample session dose-dependently reduced the total time spent on exploring the social partner and objects in the adult rats, and had a significantly larger effect in the females than in the males. MK-801 also dose-dependently increased motor activity. However, it did not alter the object, spatial and social recognitions. These findings indicate that the new triple recognition paradigm is capable of recording the object, spatial location and social recognition together and revealing potential sex and age differences. This paradigm is also useful for the study of object and social exploration concurrently and can be used to evaluate cognition-altering drugs in various stages of recognition memories. Copyright © 2018. Published by Elsevier Inc.

Comparison of RCS prediction techniques, computations and measurements

NASA Astrophysics Data System (ADS)

Brand, M. G. E.; Vanewijk, L. J.; Klinker, F.; Schippers, H.

1992-07-01

Three calculation methods to predict radar cross sections (RCS) of three dimensional objects are evaluated by computing the radar cross sections of a generic wing inlet configuration. The following methods are applied: a three dimensional high frequency method, a three dimensional boundary element method, and a two dimensional finite difference time domain method. The results of the computations are compared with the data of measurements.

Three-Dimensional Messages for Interstellar Communication

NASA Astrophysics Data System (ADS)

Vakoch, Douglas A.

One of the challenges facing independently evolved civilizations separated by interstellar distances is to communicate information unique to one civilization. One commonly proposed solution is to begin with two-dimensional pictorial representations of mathematical concepts and physical objects, in the hope that this will provide a foundation for overcoming linguistic barriers. However, significant aspects of such representations are highly conventional, and may not be readily intelligible to a civilization with different conventions. The process of teaching conventions of representation may be facilitated by the use of three-dimensional representations redundantly encoded in multiple formats (e.g., as both vectors and as rasters). After having illustrated specific conventions for representing mathematical objects in a three-dimensional space, this method can be used to describe a physical environment shared by transmitter and receiver: a three-dimensional space defined by the transmitter--receiver axis, and containing stars within that space. This method can be extended to show three-dimensional representations varying over time. Having clarified conventions for representing objects potentially familiar to both sender and receiver, novel objects can subsequently be depicted. This is illustrated through sequences showing interactions between human beings, which provide information about human behavior and personality. Extensions of this method may allow the communication of such culture-specific features as aesthetic judgments and religious beliefs. Limitations of this approach will be noted, with specific reference to ETI who are not primarily visual.

The extraction and use of facial features in low bit-rate visual communication.

PubMed

Pearson, D

1992-01-29

A review is given of experimental investigations by the author and his collaborators into methods of extracting binary features from images of the face and hands. The aim of the research has been to enable deaf people to communicate by sign language over the telephone network. Other applications include model-based image coding and facial-recognition systems. The paper deals with the theoretical postulates underlying the successful experimental extraction of facial features. The basic philosophy has been to treat the face as an illuminated three-dimensional object and to identify features from characteristics of their Gaussian maps. It can be shown that in general a composite image operator linked to a directional-illumination estimator is required to accomplish this, although the latter can often be omitted in practice.

Stable orthogonal local discriminant embedding for linear dimensionality reduction.

PubMed

Gao, Quanxue; Ma, Jingjie; Zhang, Hailin; Gao, Xinbo; Liu, Yamin

2013-07-01

Manifold learning is widely used in machine learning and pattern recognition. However, manifold learning only considers the similarity of samples belonging to the same class and ignores the within-class variation of data, which will impair the generalization and stableness of the algorithms. For this purpose, we construct an adjacency graph to model the intraclass variation that characterizes the most important properties, such as diversity of patterns, and then incorporate the diversity into the discriminant objective function for linear dimensionality reduction. Finally, we introduce the orthogonal constraint for the basis vectors and propose an orthogonal algorithm called stable orthogonal local discriminate embedding. Experimental results on several standard image databases demonstrate the effectiveness of the proposed dimensionality reduction approach.

Fourier optics of constant-thickness three-dimensional objects on the basis of diffraction models

NASA Astrophysics Data System (ADS)

Chugui, Yu. V.

2017-09-01

Results of investigations of diffraction phenomena on constant-thickness three-dimensional objects with flat inner surfaces (thick plates) are summarized on the basis of our constructive theory of their calculation as applied to dimensional inspection. It is based on diffraction models of 3D objects with the use of equivalent diaphragms (distributions), which allow the Kirchhoff-Fresnel approximation to be effectively used. In contrast to available rigorous and approximate methods, the present approach does not require cumbersome calculations; it is a clearly arranged method, which ensures sufficient accuracy for engineering applications. It is found that the fundamental diffraction parameter for 3D objects of constant thickness d is the critical diffraction angle {θ _{cr}} = √ {λ /d} at which the effect of three-dimensionality on the spectrum of the 3D object becomes appreciable. Calculated Fraunhofer diffraction patterns (spectra) and images of constant-thickness 3D objects with absolutely absorbing, absolutely reflecting, and gray internal faces are presented. It is demonstrated that selection of 3D object fragments can be performed by choosing an appropriate configuration of the wave illuminating the object (plane normal or inclined waves, spherical waves).

A rudimentary database for three-dimensional objects using structural representation

NASA Technical Reports Server (NTRS)

Sowers, James P.

1987-01-01

A database which enables users to store and share the description of three-dimensional objects in a research environment is presented. The main objective of the design is to make it a compact structure that holds sufficient information to reconstruct the object. The database design is based on an object representation scheme which is information preserving, reasonably efficient, and yet economical in terms of the storage requirement. The determination of the needed data for the reconstruction process is guided by the belief that it is faster to do simple computations to generate needed data/information for construction than to retrieve everything from memory. Some recent techniques of three-dimensional representation that influenced the design of the database are discussed. The schema for the database and the structural definition used to define an object are given. The user manual for the software developed to create and maintain the contents of the database is included.

Concealed object segmentation and three-dimensional localization with passive millimeter-wave imaging

NASA Astrophysics Data System (ADS)

Yeom, Seokwon

2013-05-01

Millimeter waves imaging draws increasing attention in security applications for weapon detection under clothing. In this paper, concealed object segmentation and three-dimensional localization schemes are reviewed. A concealed object is segmented by the k-means algorithm. A feature-based stereo-matching method estimates the longitudinal distance of the concealed object. The distance is estimated by the discrepancy between the corresponding centers of the segmented objects. Experimental results are provided with the analysis of the depth resolution.

Accurate color synthesis of three-dimensional objects in an image

NASA Astrophysics Data System (ADS)

Xin, John H.; Shen, Hui-Liang

2004-05-01

Our study deals with color synthesis of a three-dimensional object in an image; i.e., given a single image, a target color can be accurately mapped onto the object such that the color appearance of the synthesized object closely resembles that of the actual one. As it is almost impossible to acquire the complete geometric description of the surfaces of an object in an image, this study attempted to recover the implicit description of geometry for the color synthesis. The description was obtained from either a series of spectral reflectances or the RGB signals at different surface positions on the basis of the dichromatic reflection model. The experimental results showed that this implicit image-based representation is related to the object geometry and is sufficient for accurate color synthesis of three-dimensional objects in an image. The method established is applicable to the color synthesis of both rigid and deformable objects and should contribute to color fidelity in virtual design, manufacturing, and retailing.

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

2016-01-01

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. PMID:27347978

Three-Dimensional Printing of a Scalable Molecular Model and Orbital Kit for Organic Chemistry Teaching and Learning

ERIC Educational Resources Information Center

Penny, Matthew R.; Cao, Zi Jing; Patel, Bhaven; dos Santos, Bruno Sil; Asquith, Christopher R. M.; Szulc, Blanka R.; Rao, Zenobia X.; Muwaffak, Zaid; Malkinson, John P.; Hilton, Stephen T.

2017-01-01

Three-dimensional (3D) chemical models are a well-established learning tool used to enhance the understanding of chemical structures by converting two-dimensional paper or screen outputs into realistic three-dimensional objects. While commercial atom model kits are readily available, there is a surprising lack of large molecular and orbital models…

Recognition of sign language with an inertial sensor-based data glove.

PubMed

Kim, Kyung-Won; Lee, Mi-So; Soon, Bo-Ram; Ryu, Mun-Ho; Kim, Je-Nam

2015-01-01

Communication between people with normal hearing and hearing impairment is difficult. Recently, a variety of studies on sign language recognition have presented benefits from the development of information technology. This study presents a sign language recognition system using a data glove composed of 3-axis accelerometers, magnetometers, and gyroscopes. Each data obtained by the data glove is transmitted to a host application (implemented in a Window program on a PC). Next, the data is converted into angle data, and the angle information is displayed on the host application and verified by outputting three-dimensional models to the display. An experiment was performed with five subjects, three females and two males, and a performance set comprising numbers from one to nine was repeated five times. The system achieves a 99.26% movement detection rate, and approximately 98% recognition rate for each finger's state. The proposed system is expected to be a more portable and useful system when this algorithm is applied to smartphone applications for use in some situations such as in emergencies.

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

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

PubMed

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

2017-09-01

In tests of object recognition, individual differences typically correlate modestly but nontrivially across familiar categories (e.g. cars, faces, shoes, birds, mushrooms). In theory, these correlations could reflect either global, non-specific mechanisms, such as general intelligence (IQ), or more specific mechanisms. Here, we introduce two separate methods for effectively capturing category-general performance variation, one that uses novel objects and one that uses familiar objects. In each case, we show that category-general performance variance is unrelated to IQ, thereby implicating more specific mechanisms. The first approach examines three newly developed novel object memory tests (NOMTs). We predicted that NOMTs would exhibit more shared, category-general variance than familiar object memory tests (FOMTs) because novel objects, unlike familiar objects, lack category-specific environmental influences (e.g. exposure to car magazines or botany classes). This prediction held, and remarkably, virtually none of the substantial shared variance among NOMTs was explained by IQ. Also, while NOMTs correlated nontrivially with two FOMTs (faces, cars), these correlations were smaller than among NOMTs and no larger than between the face and car tests themselves, suggesting that the category-general variance captured by NOMTs is specific not only relative to IQ, but also, to some degree, relative to both face and car recognition. The second approach averaged performance across multiple FOMTs, which we predicted would increase category-general variance by averaging out category-specific factors. This prediction held, and as with NOMTs, virtually none of the shared variance among FOMTs was explained by IQ. Overall, these results support the existence of object recognition mechanisms that, though category-general, are specific relative to IQ and substantially separable from face and car recognition. They also add sensitive, well-normed NOMTs to the tools available to study object recognition. Copyright © 2017 Elsevier B.V. All rights reserved.

Active confocal imaging for visual prostheses

PubMed Central

Jung, Jae-Hyun; Aloni, Doron; Yitzhaky, Yitzhak; Peli, Eli

2014-01-01

There are encouraging advances in prosthetic vision for the blind, including retinal and cortical implants, and other “sensory substitution devices” that use tactile or electrical stimulation. However, they all have low resolution, limited visual field, and can display only few gray levels (limited dynamic range), severely restricting their utility. To overcome these limitations, image processing or the imaging system could emphasize objects of interest and suppress the background clutter. We propose an active confocal imaging system based on light-field technology that will enable a blind user of any visual prosthesis to efficiently scan, focus on, and “see” only an object of interest while suppressing interference from background clutter. The system captures three-dimensional scene information using a light-field sensor and displays only an in-focused plane with objects in it. After capturing a confocal image, a de-cluttering process removes the clutter based on blur difference. In preliminary experiments we verified the positive impact of confocal-based background clutter removal on recognition of objects in low resolution and limited dynamic range simulated phosphene images. Using a custom-made multiple-camera system, we confirmed that the concept of a confocal de-cluttered image can be realized effectively using light field imaging. PMID:25448710

Three-dimensional printing in surgery: a review of current surgical applications.

PubMed

Malik, Hammad H; Darwood, Alastair R J; Shaunak, Shalin; Kulatilake, Priyantha; El-Hilly, Abdulrahman A; Mulki, Omar; Baskaradas, Aroon

2015-12-01

Three-dimensional printing (3DP) is gaining increasing recognition as a technique that will transform the landscape of surgical practice. It allows for the rapid conversion of anatomic images into physical objects, which are being used across a variety of surgical specialties. It has been unclear which groups are leading the way in coming up with novel ways of using the technology and what specifically the technology is being used for. The aim of this article was to review the current applications of 3DP in modern surgical practice. An electronic search was carried out in MEDLINE, EMBASE, and PsycINFO for terms related to 3DP. These were then screened for relevance and practical applications of the technology in surgery. Four hundred eighty-eight articles were initially found, and these were eventually narrowed down to 93 full-text articles. It was determined that there were three main areas in which the technology is being used to print: (1) anatomic models, (2) surgical instruments, and (3) implants and prostheses. Different specialties are at different stages in the use of the technology. The costs involved with implementing the technology and time taken for printing are important factors to consider before widespread use. For the foreseeable future, this is an exciting and interesting technology with the capacity to radically change health care and revolutionize modern surgery. Copyright © 2015 Elsevier Inc. All rights reserved.

Clustering by reordering of similarity and Laplacian matrices: Application to galaxy clusters

NASA Astrophysics Data System (ADS)

Mahmoud, E.; Shoukry, A.; Takey, A.

2018-04-01

Similarity metrics, kernels and similarity-based algorithms have gained much attention due to their increasing applications in information retrieval, data mining, pattern recognition and machine learning. Similarity Graphs are often adopted as the underlying representation of similarity matrices and are at the origin of known clustering algorithms such as spectral clustering. Similarity matrices offer the advantage of working in object-object (two-dimensional) space where visualization of clusters similarities is available instead of object-features (multi-dimensional) space. In this paper, sparse ɛ-similarity graphs are constructed and decomposed into strong components using appropriate methods such as Dulmage-Mendelsohn permutation (DMperm) and/or Reverse Cuthill-McKee (RCM) algorithms. The obtained strong components correspond to groups (clusters) in the input (feature) space. Parameter ɛi is estimated locally, at each data point i from a corresponding narrow range of the number of nearest neighbors. Although more advanced clustering techniques are available, our method has the advantages of simplicity, better complexity and direct visualization of the clusters similarities in a two-dimensional space. Also, no prior information about the number of clusters is needed. We conducted our experiments on two and three dimensional, low and high-sized synthetic datasets as well as on an astronomical real-dataset. The results are verified graphically and analyzed using gap statistics over a range of neighbors to verify the robustness of the algorithm and the stability of the results. Combining the proposed algorithm with gap statistics provides a promising tool for solving clustering problems. An astronomical application is conducted for confirming the existence of 45 galaxy clusters around the X-ray positions of galaxy clusters in the redshift range [0.1..0.8]. We re-estimate the photometric redshifts of the identified galaxy clusters and obtain acceptable values compared to published spectroscopic redshifts with a 0.029 standard deviation of their differences.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

Constraints in distortion-invariant target recognition system simulation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Multiple mechanisms underlie defective recognition of melanoma cells cultured in three-dimensional architectures by antigen-specific cytotoxic T lymphocytes.

PubMed

Feder-Mengus, C; Ghosh, S; Weber, W P; Wyler, S; Zajac, P; Terracciano, L; Oertli, D; Heberer, M; Martin, I; Spagnoli, G C; Reschner, A

2007-04-10

Cancer cells' growth in three-dimensional (3D) architectures promotes resistance to drugs, cytokines, or irradiation. We investigated effects of 3D culture as compared to monolayers (2D) on melanoma cells' recognition by tumour-associated antigen (TAA)-specific HLA-A(*)0201-restricted cytotoxic T-lymphocytes (CTL). Culture of HBL, D10 (both HLA-A(*)0201+, TAA+) and NA8 (HLA-A(*)0201+, TAA-) melanoma cells on polyHEMA-coated plates, resulted in generation of 3D multicellular tumour spheroids (MCTS). Interferon-gamma (IFN-gamma) production by HLA-A(*)0201-restricted Melan-A/MART-1(27-35) or gp 100(280-288)-specific CTL clones served as immunorecognition marker. Co-culture with melanoma MCTS, resulted in defective TAA recognition by CTL as compared to 2D as witnessed by decreased IFN-gamma production and decreased Fas Ligand, perforin and granzyme B gene expression. A multiplicity of mechanisms were potentially involved. First, MCTS per se limit CTL capacity of recognising HLA class I restricted antigens by reducing exposed cell surfaces. Second, expression of melanoma differentiation antigens is downregulated in MCTS. Third, expression of HLA class I molecules can be downregulated in melanoma MCTS, possibly due to decreased interferon-regulating factor-1 gene expression. Fourth, lactic acid production is increased in MCTS, as compared to 2D. These data suggest that melanoma cells growing in 3D, even in the absence of immune selection, feature characteristics capable of dramatically inhibiting TAA recognition by specific CTL.

Real-time spectral imaging in three spatial dimensions

NASA Astrophysics Data System (ADS)

Liu, Wenhai; Psaltis, Demetri; Barbastathis, George

2002-05-01

We report what is to our knowledge the first volume-holographic optical imaging instrument with the capability to return three-dimensional spatial as well as spectral information about semitranslucent microscopic objects in a single measurement. The four-dimensional volume-holographic microscope is characterized theoretically and experimentally by use of fluorescent microspheres as objects.

Paranemic Crossover DNA: There and Back Again.

PubMed

Wang, Xing; Chandrasekaran, Arun Richard; Shen, Zhiyong; Ohayon, Yoel P; Wang, Tong; Kizer, Megan E; Sha, Ruojie; Mao, Chengde; Yan, Hao; Zhang, Xiaoping; Liao, Shiping; Ding, Baoquan; Chakraborty, Banani; Jonoska, Natasha; Niu, Dong; Gu, Hongzhou; Chao, Jie; Gao, Xiang; Li, Yuhang; Ciengshin, Tanashaya; Seeman, Nadrian C

2018-06-18

Over the past 35 years, DNA has been used to produce various nanometer-scale constructs, nanomechanical devices, and walkers. Construction of complex DNA nanostructures relies on the creation of rigid DNA motifs. Paranemic crossover (PX) DNA is one such motif that has played many roles in DNA nanotechnology. Specifically, PX cohesion has been used to connect topologically closed molecules, to assemble a three-dimensional object, and to create two-dimensional DNA crystals. Additionally, a sequence-dependent nanodevice based on conformational change between PX and its topoisomer, JX 2 , has been used in robust nanoscale assembly lines, as a key component in a DNA transducer, and to dictate polymer assembly. Furthermore, the PX motif has recently found a new role directly in basic biology, by possibly serving as the molecular structure for double-stranded DNA homology recognition, a prominent feature of molecular biology and essential for many crucial biological processes. This review discusses the many attributes and usages of PX-DNA-its design, characteristics, applications, and potential biological relevance-and aims to accelerate the understanding of PX-DNA motif in its many roles and manifestations.

Three-dimensional imaging of artificial fingerprint by optical coherence tomography

NASA Astrophysics Data System (ADS)

Larin, Kirill V.; Cheng, Yezeng

2008-03-01

Fingerprint recognition is one of the popular used methods of biometrics. However, due to the surface topography limitation, fingerprint recognition scanners are easily been spoofed, e.g. using artificial fingerprint dummies. Thus, biometric fingerprint identification devices need to be more accurate and secure to deal with different fraudulent methods including dummy fingerprints. Previously, we demonstrated that Optical Coherence Tomography (OCT) images revealed the presence of the artificial fingerprints (made from different household materials, such as cement and liquid silicone rubber) at all times, while the artificial fingerprints easily spoofed the commercial fingerprint reader. Also we demonstrated that an analysis of the autocorrelation of the OCT images could be used in automatic recognition systems. Here, we exploited the three-dimensional (3D) imaging of the artificial fingerprint by OCT to generate vivid 3D image for both the artificial fingerprint layer and the real fingerprint layer beneath. With the reconstructed 3D image, it could not only point out whether there exists an artificial material, which is intended to spoof the scanner, above the real finger, but also could provide the hacker's fingerprint. The results of these studies suggested that Optical Coherence Tomography could be a powerful real-time noninvasive method for accurate identification of artificial fingerprints real fingerprints as well.

Compensation for Blur Requires Increase in Field of View and Viewing Time

PubMed Central

Kwon, MiYoung; Liu, Rong; Chien, Lillian

2016-01-01

Spatial resolution is an important factor for human pattern recognition. In particular, low resolution (blur) is a defining characteristic of low vision. Here, we examined spatial (field of view) and temporal (stimulus duration) requirements for blurry object recognition. The spatial resolution of an image such as letter or face, was manipulated with a low-pass filter. In experiment 1, studying spatial requirement, observers viewed a fixed-size object through a window of varying sizes, which was repositioned until object identification (moving window paradigm). Field of view requirement, quantified as the number of “views” (window repositions) for correct recognition, was obtained for three blur levels, including no blur. In experiment 2, studying temporal requirement, we determined threshold viewing time, the stimulus duration yielding criterion recognition accuracy, at six blur levels, including no blur. For letter and face recognition, we found blur significantly increased the number of views, suggesting a larger field of view is required to recognize blurry objects. We also found blur significantly increased threshold viewing time, suggesting longer temporal integration is necessary to recognize blurry objects. The temporal integration reflects the tradeoff between stimulus intensity and time. While humans excel at recognizing blurry objects, our findings suggest compensating for blur requires increased field of view and viewing time. The need for larger spatial and longer temporal integration for recognizing blurry objects may further challenge object recognition in low vision. Thus, interactions between blur and field of view should be considered for developing low vision rehabilitation or assistive aids. PMID:27622710

Influence of target reflection on three-dimensional range gated reconstruction.

PubMed

Chua, Sing Yee; Wang, Xin; Guo, Ningqun; Tan, Ching Seong

2016-08-20

The range gated technique is a promising laser ranging method that is widely used in different fields such as surveillance, industry, and military. In a range gated system, a reflected laser pulse returned from the target scene contains key information for range reconstruction, which directly affects the system performance. Therefore, it is necessary to study the characteristics and effects of the target reflection factor. In this paper, theoretical and experimental analyses are performed to investigate the influence of target reflection on three-dimensional (3D) range gated reconstruction. Based on laser detection and ranging (LADAR) and bidirectional reflection distribution function (BRDF) theory, a 3D range gated reconstruction model is derived and the effect on range accuracy is analyzed from the perspectives of target surface reflectivity and angle of laser incidence. Our theoretical and experimental study shows that the range accuracy is proportional to the target surface reflectivity, but it decreases when the angle of incidence increases to adhere to the BRDF model. The presented findings establish a comprehensive understanding of target reflection in 3D range gated reconstruction, which is of interest to various applications such as target recognition and object modeling. This paper provides a reference for future improvement to perform accurate range compensation or correction.

The Chinese Facial Emotion Recognition Database (CFERD): a computer-generated 3-D paradigm to measure the recognition of facial emotional expressions at different intensities.

PubMed

Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2012-12-30

The Chinese Facial Emotion Recognition Database (CFERD), a computer-generated three-dimensional (3D) paradigm, was developed to measure the recognition of facial emotional expressions at different intensities. The stimuli consisted of 3D colour photographic images of six basic facial emotional expressions (happiness, sadness, disgust, fear, anger and surprise) and neutral faces of the Chinese. The purpose of the present study is to describe the development and validation of CFERD with nonclinical healthy participants (N=100; 50 men; age ranging between 18 and 50 years), and to generate normative data set. The results showed that the sensitivity index d' [d'=Z(hit rate)-Z(false alarm rate), where function Z(p), p∈[0,1

Marginal Fisher analysis and its variants for human gait recognition and content- based image retrieval.

PubMed

Xu, Dong; Yan, Shuicheng; Tao, Dacheng; Lin, Stephen; Zhang, Hong-Jiang

2007-11-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for human gait recognition and content-based image retrieval (CBIR). In this paper, we present extensions of our recently proposed marginal Fisher analysis (MFA) to address these problems. For human gait recognition, we first present a direct application of MFA, then inspired by recent advances in matrix and tensor-based dimensionality reduction algorithms, we present matrix-based MFA for directly handling 2-D input in the form of gray-level averaged images. For CBIR, we deal with the relevance feedback problem by extending MFA to marginal biased analysis, in which within-class compactness is characterized only by the distances between each positive sample and its neighboring positive samples. In addition, we present a new technique to acquire a direct optimal solution for MFA without resorting to objective function modification as done in many previous algorithms. We conduct comprehensive experiments on the USF HumanID gait database and the Corel image retrieval database. Experimental results demonstrate that MFA and its extensions outperform related algorithms in both applications.

Two-Dimensional Grammars And Their Applications To Artificial Intelligence

NASA Astrophysics Data System (ADS)

Lee, Edward T.

1987-05-01

During the past several years, the concepts and techniques of two-dimensional grammars1,2 have attracted growing attention as promising avenues of approach to problems in picture generation as well as in picture description3 representation, recognition, transformation and manipulation. Two-dimensional grammar techniques serve the purpose of exploiting the structure or underlying relationships in a picture. This approach attempts to describe a complex picture in terms of their components and their relative positions. This resembles the way a sentence is described in terms of its words and phrases, and the terms structural picture recognition, linguistic picture recognition, or syntactic picture recognition are often used. By using this approach, the problem of picture recognition becomes similar to that of phrase recognition in a language. However, describing pictures using a string grammar (one-dimensional grammar), the only relation between sub-pictures and/or primitives is the concatenation; that is each picture or primitive can be connected only at the left or right. This one-dimensional relation has not been very effective in describing two-dimensional pictures. A natural generaliza-tion is to use two-dimensional grammars. In this paper, two-dimensional grammars and their applications to artificial intelligence are presented. Picture grammars and two-dimensional grammars are introduced and illustrated by examples. In particular, two-dimensional grammars for generating all possible squares and all possible rhombuses are presented. The applications of two-dimensional grammars to solving region filling problems are discussed. An algorithm for region filling using two-dimensional grammars is presented together with illustrative examples. The advantages of using this algorithm in terms of computation time are also stated. A high-level description of a two-level picture generation system is proposed. The first level is the picture primitive generation using two-dimensional grammars. The second level is picture generation using either string description or entity-relationship (ER) diagram description. Illustrative examples are also given. The advantages of ER diagram description together with its comparison to string description are also presented. The results obtained in this paper may have useful applications in artificial intelligence, robotics, expert systems, picture processing, pattern recognition, knowledge engineering and pictorial database design. Furthermore, examples related to satellite surveillance and identifications are also included.

Validation of a computer modelled forensic facial reconstruction technique using CT data from live subjects: a pilot study.

PubMed

Short, Laura J; Khambay, Balvinder; Ayoub, Ashraf; Erolin, Caroline; Rynn, Chris; Wilkinson, Caroline

2014-04-01

Human forensic facial soft tissue reconstructions are used when post-mortem deterioration makes identification difficult by usual means. The aim is to trigger recognition of the in vivo countenance of the individual by a friend or family member. A further use is in the field of archaeology. There are a number of different methods that can be applied to complete the facial reconstruction, ranging from two dimensional drawings, three dimensional clay models and now, with the advances of three dimensional technology, three dimensional computerised modelling. Studies carried out to assess the accuracy of facial reconstructions have produced variable results over the years. Advances in three dimensional imaging techniques in the field of oral and maxillofacial surgery, particularly cone beam computed tomography (CBCT), now provides an opportunity to utilise the data of live subjects and assess the accuracy of the three dimensional computerised facial reconstruction technique. The aim of this study was to assess the accuracy of a computer modelled facial reconstruction technique using CBCT data from live subjects. This retrospective pilot study was carried out at the Glasgow Dental Hospital Orthodontic Department and the Centre of Anatomy and Human Identification, Dundee University School of Life Sciences. Ten patients (5 male and 5 female; mean age 23 years) with mild skeletal discrepancies with pre-surgical cone beam CT data (CBCT) were included in this study. The actual and forensic reconstruction soft tissues were analysed using 3D software to look at differences between landmarks, linear and angular measurements and surface meshes. There were no statistical differences for 18 out of the 23 linear and 7 out of 8 angular measurements between the reconstruction and the target (p<0.05). The use of Procrustes superimposition has highlighted potential problems with soft tissue depth and anatomical landmarks' position. Surface mesh analysis showed that this virtual sculpture technique can be objectively assessed using the distance between the meshes. This study found that the percentage of faces with less than ±2.5mm error ranged from 56% to 90%. This may be improved if Procrustes superimposition could be applied to all the mesh points rather than specific landmarks. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

Learning object-to-class kernels for scene classification.

PubMed

Zhang, Lei; Zhen, Xiantong; Shao, Ling

2014-08-01

High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

Studying the Sky/Planets Can Drown You in Images: Machine Learning Solutions at JPL/Caltech

NASA Technical Reports Server (NTRS)

Fayyad, U. M.

1995-01-01

JPL is working to develop a domain-independent system capable of small-scale object recognition in large image databases for science analysis. Two applications discussed are the cataloging of three billion sky objects in the Sky Image Cataloging and Analysis Tool (SKICAT) and the detection of possibly one million small volcanoes visible in the Magellan synthetic aperture radar images of Venus (JPL Adaptive Recognition Tool, JARTool).

[A case of carbon monoxide poisoning by explosion of coal mine presenting as visual agnosia: re-evaluation after 40 years].

PubMed

Takaiwa, Akiko; Yamashita, Kenichiro; Nomura, Takuo; Shida, Kenshiro; Taniwaki, Takayuki

2005-11-01

We re-evaluated a case of carbon monoxide poisoning presenting as visual agnosia who had been injured by explosion of Miike-Mikawa coal mine 40 years ago. In an early stage, his main neuropsychological symptoms were visual agnosia, severe anterograde amnesia, alexia, agraphia, constructional apraxia, left hemispatial neglect and psychic paralysis of gaze, in addition to pyramidal and extra pyramidal signs. At the time of re-evaluation after 40 years, he still showed visual agnosia associated with agraphia and constructional apraxia. Concerning visual agnosia, recognition of the real object was preserved, while recognition of object photographs and picture was impaired. Thus, this case was considered to have picture agnosia as he could not recognize the object by pictorial cues on the second dimensional space. MRI examination revealed low signal intensity lesions and cortical atrophy in the bilateral parieto-occipital lobes on T1-weighted images. Therefore, the bilateral parieto-occipital lesions are likely to be responsible for his picture agnosia.

Relevance feedback-based building recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Allinson, Nigel M.

2010-07-01

Building recognition is a nontrivial task in computer vision research which can be utilized in robot localization, mobile navigation, etc. However, existing building recognition systems usually encounter the following two problems: 1) extracted low level features cannot reveal the true semantic concepts; and 2) they usually involve high dimensional data which require heavy computational costs and memory. Relevance feedback (RF), widely applied in multimedia information retrieval, is able to bridge the gap between the low level visual features and high level concepts; while dimensionality reduction methods can mitigate the high-dimensional problem. In this paper, we propose a building recognition scheme which integrates the RF and subspace learning algorithms. Experimental results undertaken on our own building database show that the newly proposed scheme appreciably enhances the recognition accuracy.

In vitro development of preimplantation porcine embryos using alginate hydrogels as a three-dimensional extracellular matrix

USDA-ARS?s Scientific Manuscript database

Between day 10 and 12 of gestation, porcine embryos undergo a dramatic morphological change, known as elongation, with a corresponding increase in estrogen production for maternal recognition of pregnancy. Elongation deficiencies contribute to ~20% of embryonic loss, but exact mechanisms of elongati...

Bimodal benefits on objective and subjective outcomes for adult cochlear implant users.

PubMed

Heo, Ji-Hye; Lee, Jae-Hee; Lee, Won-Sang

2013-09-01

Given that only a few studies have focused on the bimodal benefits on objective and subjective outcomes and emphasized the importance of individual data, the present study aimed to measure the bimodal benefits on the objective and subjective outcomes for adults with cochlear implant. Fourteen listeners with bimodal devices were tested on the localization and recognition abilities using environmental sounds, 1-talker, and 2-talker speech materials. The localization ability was measured through an 8-loudspeaker array. For the recognition measures, listeners were asked to repeat the sentences or say the environmental sounds the listeners heard. As a subjective questionnaire, three domains of Korean-version of Speech, Spatial, Qualities of Hearing scale (K-SSQ) were used to explore any relationships between objective and subjective outcomes. Based on the group-mean data, the bimodal hearing enhanced both localization and recognition regardless of test material. However, the inter- and intra-subject variability appeared to be large across test materials for both localization and recognition abilities. Correlation analyses revealed that the relationships were not always consistent between the objective outcomes and the subjective self-reports with bimodal devices. Overall, this study supports significant bimodal advantages on localization and recognition measures, yet the large individual variability in bimodal benefits should be considered carefully for the clinical assessment as well as counseling. The discrepant relations between objective and subjective results suggest that the bimodal benefits in traditional localization or recognition measures might not necessarily correspond to the self-reported subjective advantages in everyday listening environments.

Three-dimensional confocal microscopy of the living cornea and ocular lens

NASA Astrophysics Data System (ADS)

Masters, Barry R.

1991-07-01

The three-dimensional reconstruction of the optic zone of the cornea and the ocular crystalline lens has been accomplished using confocal microscopy and volume rendering computer techniques. A laser scanning confocal microscope was used in the reflected light mode to obtain the two-dimensional images from the cornea and the ocular lens of a freshly enucleated rabbit eye. The light source was an argon ion laser with a 488 nm wavelength. The microscope objective was a Leitz X25, NA 0.6 water immersion lens. The 400 micron thick cornea was optically sectioned into 133 three micron sections. The semi-transparent cornea and the in-situ ocular lens was visualized as high resolution, high contrast two-dimensional images. The structures observed in the cornea include: superficial epithelial cells and their nuclei, basal epithelial cells and their 'beaded' cell borders, basal lamina, nerve plexus, nerve fibers, nuclei of stromal keratocytes, and endothelial cells. The structures observed in the in- situ ocular lens include: lens capsule, lens epithelial cells, and individual lens fibers. The three-dimensional data sets of the cornea and the ocular lens were reconstructed in the computer using volume rendering techniques. Stereo pairs were also created of the two- dimensional ocular images for visualization. The stack of two-dimensional images was reconstructed into a three-dimensional object using volume rendering techniques. This demonstration of the three-dimensional visualization of the intact, enucleated eye provides an important step toward quantitative three-dimensional morphometry of the eye. The important aspects of three-dimensional reconstruction are discussed.

Roots and decompositions of three-dimensional topological objects

NASA Astrophysics Data System (ADS)

Matveev, Sergei V.

2012-06-01

In 1942 M.H.A. Newman formulated and proved a simple lemma of great importance for various fields of mathematics, including algebra and the theory of Gröbner-Shirshov bases. Later it was called the Diamond Lemma, since its key construction was illustrated by a diamond-shaped diagram. In 2005 the author suggested a new version of this lemma suitable for topological applications. This paper gives a survey of results on the existence and uniqueness of prime decompositions of various topological objects: three-dimensional manifolds, knots in thickened surfaces, knotted graphs, three-dimensional orbifolds, and knotted theta-curves in three-dimensional manifolds. As it turned out, all these topological objects admit a prime decomposition, although it is not unique in some cases (for example, in the case of orbifolds). For theta-curves and knots of geometric degree 1 in a thickened torus, the algebraic structure of the corresponding semigroups can be completely described. In both cases the semigroups are quotients of free groups by explicit commutation relations. Bibliography: 33 titles.

Development of Three-Dimensional Object Completion in Infancy

ERIC Educational Resources Information Center

Soska, Kasey C.; Johnson, Scott P.

2008-01-01

Three-dimensional (3D) object completion was investigated by habituating 4- and 6-month-old infants (n = 24 total) with a computer-generated wedge stimulus that pivoted 15[degrees], providing only a limited view. Two displays, rotating 360[degrees], were then shown: a complete, solid volume and an incomplete, hollow form composed only of the sides…

Optical encryption of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography

NASA Astrophysics Data System (ADS)

Wang, Ying; Liu, Qi; Wang, Jun; Wang, Qiong-Hua

2018-03-01

We present an optical encryption method of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography. By modifying the Mach–Zehnder interferometer, the interference of the multiple objects beams and the one reference beam is used to simultaneously encrypt multiple objects into a ciphertext. During decryption, each three-dimensional object can be decrypted independently without having to decrypt other objects. Since the single-pixel digital holography based on compressive sensing theory is introduced, the encrypted data of this method is effectively reduced. In addition, recording fewer encrypted data can greatly reduce the bandwidth of network transmission. Moreover, the compressive sensing essentially serves as a secret key that makes an intruder attack invalid, which means that the system is more secure than the conventional encryption method. Simulation results demonstrate the feasibility of the proposed method and show that the system has good security performance. Project supported by the National Natural Science Foundation of China (Grant Nos. 61405130 and 61320106015).

The application of holography as a real-time three-dimensional motion picture camera

NASA Technical Reports Server (NTRS)

Kurtz, R. L.

1973-01-01

A historical introduction to holography is presented, as well as a basic description of sideband holography for stationary objects. A brief theoretical development of both time-dependent and time-independent holography is also provided, along with an analytical and intuitive discussion of a unique holographic arrangement which allows the resolution of front surface detail from an object moving at high speeds. As an application of such a system, a real-time three-dimensional motion picture camera system is discussed and the results of a recent demonstration of the world's first true three-dimensional motion picture are given.

[Application Progress of Three-dimensional Laser Scanning Technology in Medical Surface Mapping].

PubMed

Zhang, Yonghong; Hou, He; Han, Yuchuan; Wang, Ning; Zhang, Ying; Zhu, Xianfeng; Wang, Mingshi

2016-04-01

The booming three-dimensional laser scanning technology can efficiently and effectively get spatial three-dimensional coordinates of the detected object surface and reconstruct the image at high speed,high precision and large capacity of information.Non-radiation,non-contact and the ability of visualization make it increasingly popular in three-dimensional surface medical mapping.This paper reviews the applications and developments of three-dimensional laser scanning technology in medical field,especially in stomatology,plastic surgery and orthopedics.Furthermore,the paper also discusses the application prospects in the future as well as the biomedical engineering problems it would encounter with.

Intersection of three-dimensional geometric surfaces

NASA Technical Reports Server (NTRS)

Crisp, V. K.; Rehder, J. J.; Schwing, J. L.

1985-01-01

Calculating the line of intersection between two three-dimensional objects and using the information to generate a third object is a key element in a geometry development system. Techniques are presented for the generation of three-dimensional objects, the calculation of a line of intersection between two objects, and the construction of a resultant third object. The objects are closed surfaces consisting of adjacent bicubic parametric patches using Bezier basis functions. The intersection determination involves subdividing the patches that make up the objects until they are approximately planar and then calculating the intersection between planes. The resulting straight-line segments are connected to form the curve of intersection. The polygons in the neighborhood of the intersection are reconstructed and put back into the Bezier representation. A third object can be generated using various combinations of the original two. Several examples are presented. Special cases and problems were encountered, and the method for handling them is discussed. The special cases and problems included intersection of patch edges, gaps between adjacent patches because of unequal subdivision, holes, or islands within patches, and computer round-off error.

Bimodal Benefits on Objective and Subjective Outcomes for Adult Cochlear Implant Users

PubMed Central

Heo, Ji-Hye; Lee, Won-Sang

2013-01-01

Background and Objectives Given that only a few studies have focused on the bimodal benefits on objective and subjective outcomes and emphasized the importance of individual data, the present study aimed to measure the bimodal benefits on the objective and subjective outcomes for adults with cochlear implant. Subjects and Methods Fourteen listeners with bimodal devices were tested on the localization and recognition abilities using environmental sounds, 1-talker, and 2-talker speech materials. The localization ability was measured through an 8-loudspeaker array. For the recognition measures, listeners were asked to repeat the sentences or say the environmental sounds the listeners heard. As a subjective questionnaire, three domains of Korean-version of Speech, Spatial, Qualities of Hearing scale (K-SSQ) were used to explore any relationships between objective and subjective outcomes. Results Based on the group-mean data, the bimodal hearing enhanced both localization and recognition regardless of test material. However, the inter- and intra-subject variability appeared to be large across test materials for both localization and recognition abilities. Correlation analyses revealed that the relationships were not always consistent between the objective outcomes and the subjective self-reports with bimodal devices. Conclusions Overall, this study supports significant bimodal advantages on localization and recognition measures, yet the large individual variability in bimodal benefits should be considered carefully for the clinical assessment as well as counseling. The discrepant relations between objective and subjective results suggest that the bimodal benefits in traditional localization or recognition measures might not necessarily correspond to the self-reported subjective advantages in everyday listening environments. PMID:24653909

Algebraic Thinking through Origami.

ERIC Educational Resources Information Center

Higginson, William; Colgan, Lynda

2001-01-01

Describes the use of paper folding to create a rich environment for discussing algebraic concepts. Explores the effect that changing the dimensions of two-dimensional objects has on the volume of related three-dimensional objects. (Contains 13 references.) (YDS)

Influence of Objective Three-Dimensional Measures and Movement Images on Surgeon Treatment Planning for Lip Revision Surgery

PubMed Central

Trotman, Carroll-Ann; Phillips, Ceib; Faraway, Julian J.; Hartman, Terry; van Aalst, John A.

2013-01-01

Objective To determine whether a systematic evaluation of facial soft tissues of patients with cleft lip and palate, using facial video images and objective three-dimensional measurements of movement, change surgeons’ treatment plans for lip revision surgery. Design Prospective longitudinal study. Setting The University of North Carolina School of Dentistry. Patients, Participants A group of patients with repaired cleft lip and palate (n = 21), a noncleft control group (n = 37), and surgeons experienced in cleft care. Interventions Lip revision. Main Outcome Measures (1) facial photographic images; (2) facial video images during animations; (3) objective three-dimensional measurements of upper lip movement based on z scores; and (4) objective dynamic and visual three-dimensional measurement of facial soft tissue movement. Results With the use of the video images plus objective three-dimensional measures, changes were made to the problem list of the surgical treatment plan for 86% of the patients (95% confidence interval, 0.64 to 0.97) and the surgical goals for 71% of the patients (95% confidence interval, 0.48 to 0.89). The surgeon group varied in the percentage of patients for whom the problem list was modified, ranging from 24% (95% confidence interval, 8% to 47%) to 48% (95% confidence interval, 26% to 70%) of patients, and the percentage for whom the surgical goals were modified, ranging from 14% (94% confidence interval, 3% to 36%) to 48% (95% confidence interval, 26% to 70%) of patients. Conclusions For all surgeons, the additional assessment components of the systematic valuation resulted in a change in clinical decision making for some patients. PMID:23855676

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

How the brain assigns a neural tag to arbitrary points in a high-dimensional space

NASA Astrophysics Data System (ADS)

Stevens, Charles

Brains in almost all organisms need to deal with very complex stimuli. For example, most mammals are very good at face recognition, and faces are very complex objects indeed. For example, modern face recognition software represents a face as a point in a 10,000 dimensional space. Every human must be able to learn to recognize any of the 7 billion faces in the world, and can recognize familiar faces after a display of the face is viewed for only a few hundred milliseconds. Because we do not understand how faces are assigned locations in a high-dimensional space by the brain, attacking the problem of how face recognition is accomplished is very difficult. But a much easier problem of the same sort can be studied for odor recognition. For the mouse, each odor is assigned a point in a 1000 dimensional space, and the fruit fly assigns any odor a location in only a 50 dimensional space. A fly has about 50 distinct types of odorant receptor neurons (ORNs), each of which produce nerve impulses at a specific rate for each different odor. This pattern of firing produced across 50 ORNs is called `a combinatorial odor code', and this code assigns every odor a point in a 50 dimensional space that is used to identify the odor. In order to learn the odor, the brain must alter the strength of synapses. The combinatorial code cannot itself by used to change synaptic strength because all odors use same neurons to form the code, and so all synapses would be changed for any odor and the odors could not be distinguished. In order to learn an odor, the brain must assign a set of neurons - the odor tag - that have the property that these neurons (1) should make use of all of the information available about the odor, and (2) insure that any two tags overlap as little as possible (so one odor does not modify synapses used by other odors). In the talk, I will explain how the olfactory system of both the fruit fly and the mouse produce a tag for each odor that has these two properties. Supported by NSF.

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

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

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

Accurate landmarking of three-dimensional facial data in the presence of facial expressions and occlusions using a three-dimensional statistical facial feature model.

PubMed

Zhao, Xi; Dellandréa, Emmanuel; Chen, Liming; Kakadiaris, Ioannis A

2011-10-01

Three-dimensional face landmarking aims at automatically localizing facial landmarks and has a wide range of applications (e.g., face recognition, face tracking, and facial expression analysis). Existing methods assume neutral facial expressions and unoccluded faces. In this paper, we propose a general learning-based framework for reliable landmark localization on 3-D facial data under challenging conditions (i.e., facial expressions and occlusions). Our approach relies on a statistical model, called 3-D statistical facial feature model, which learns both the global variations in configurational relationships between landmarks and the local variations of texture and geometry around each landmark. Based on this model, we further propose an occlusion classifier and a fitting algorithm. Results from experiments on three publicly available 3-D face databases (FRGC, BU-3-DFE, and Bosphorus) demonstrate the effectiveness of our approach, in terms of landmarking accuracy and robustness, in the presence of expressions and occlusions.

Naturalizing semiotics: The triadic sign of Charles Sanders Peirce as a systems property.

PubMed

Kilstrup, Mogens

2015-12-01

The father of pragmatism, Charles Sanders Peirce, gave in 1903 the following definition of a sign: "A Sign, or Representamen, is a First which stands in such a genuine triadic relation to a Second, called its Object, as to be capable of determining a Third, called its Interpretant, to assume the same triadic relation to its Object in which it stands itself to the same Object. The triadic relation is genuine, that is its three members are bound together by it in a way that does not consist in any complexus of dyadic relations". Despite its cult status and its pragmatic foundation, the Peircean sign has never revealed its true potential by being integrated into a formal system. In the present report, a reconstruction of the sign model is presented, which may at first appear somewhat obvious and superficial. However by use of the reconstructed model, the above statement and the majority of Peirce's other statements about the nature of signs fall into place. Instead of defining three links between Object (O), Representamen (R), and Interpretant (I), the sign is described as having a single three-dimensional link, specifying its location in a three dimensional (O,R,I) linkage space. To understand and explain sign function, the process of sign utilization (semiosis) has to be divided into two temporally separated phases, a sign-establishment phase where a three-dimensional link (Ψ(O,R,I)) is formed between three sign elements, and a later sign-interpretation phase where the established linkage is used for inferring significance to a novel phenomenon, if this satisfies the criteria for being a Representamen for the sign. Numerous statements from Peirce indicate that he used a two-staged semiosis paradigm although he did not state that explicitly. The three-dimensional model was primarily constructed for use in biosemiotics, as an exploratory frame for mapping the evolutionary establishment of sign links, which logically must have preceded the fixation of any regulatory process in molecular biological systems. It became clear, however, that the model is able to clarify many of the difficult explanations offered by Peirce about his sign model. I make no claim that Peirce used a similar type of three-dimensional model, because he explicitly used the chemical atom as naturalization (natural scientific explanation) for his sign model, an interesting but problematic analogy. In order to discuss common versus specific semiotic scaffolds for molecular biosemiotics, biosemiotics and semiotics proper, I start with a generic definition of the three-dimensional sign system, using human semiosis as examples. After this, the major part of the paper, I define the specific biochemical and evolutionary scaffolds that is used for obtaining the evolutionary memory that is needed for sign establishment. To exemplify semiosis according to the present model I present a typical situation where a Representamen (RE) and an object (OE) in the establishment phase are frequently encountered together by a sign interpreter. The process that links specific Representamens to specific Objects will first involve the recognition of the specific traits that distinguish the two sign elements. Subsequently the establishment process leads to the creation of a specific systems-state, called the Interpretant, which links the two traits in a way that allows retrieval of the information (a memory function). During a later interpretation phase, a hypothetical Object will be inferred by the interpreter when a Representamen (RI) harboring the required characteristics is encountered. This inference happens through a memory retrieval process, irrespective of the fact that relevant Objects of the sign may never be encountered after establishment. A simplified scheme for computer neural network algorithms is introduced as an example of such a system. Since the Peircean sign according to this definition is a systems property, there can be no sign without a sign interpreting systems or without some kind of memory function. A sign interpreter will thus harbor a semiotic scaffold that consists of at least an input sensor and an interpreting system coupled to a memory function. Further border conditions for semiotic scaffolds will be introduced. Peirce published a comprehensive sign definition system, but he allowed only ten sign classes, selected from the twenty-seven sign classes that result from his three main subdivisions, each containing three classes. His allowed sign classes are here identified as those which do not infer more significance during interpretation than was warranted during establishment. The excluded sign classes are either undefinable in his system or are of such a nature that the objects during interpretation are inferred to be much more significant than what was warranted during establishment. Occult signs are of these forbidden free-wheeling types, and it is postulated that they were omitted because Peirce defined his sign classes for use in a novel sign based logical system, where such over-signification would be detrimental. Copyright © 2015. Published by Elsevier Ltd.

Recognition Memory for Realistic Synthetic Faces

PubMed Central

Yotsumoto, Yuko; Kahana, Michael J.; Wilson, Hugh R.; Sekuler, Robert

2006-01-01

A series of experiments examined short-term recognition memory for trios of briefly-presented, synthetic human faces derived from three real human faces. The stimuli were graded series of faces, which differed by varying known amounts from the face of the average female. Faces based on each of the three real faces were transformed so as to lie along orthogonal axes in a 3-D face space. Experiment 1 showed that the synthetic faces' perceptual similarity stucture strongly influenced recognition memory. Results were fit by NEMo, a noisy exemplar model of perceptual recognition memory. The fits revealed that recognition memory was influenced both by the similarity of the probe to series items, and by the similarities among the series items themselves. Non-metric multi-dimensional scaling (MDS) showed that faces' perceptual representations largely preserved the 3-D space in which the face stimuli were arrayed. NEMo gave a better account of the results when similarity was defined as perceptual, MDS similarity rather than physical proximity of one face to another. Experiment 2 confirmed the importance of within-list homogeneity directly, without mediation of a model. We discuss the affinities and differences between visual memory for synthetic faces and memory for simpler stimuli. PMID:17948069

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

PubMed

Gaston, P C; Lozano-Perez, T

1984-03-01

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

A reconstruction algorithm for three-dimensional object-space data using spatial-spectral multiplexing

NASA Astrophysics Data System (ADS)

Wu, Zhejun; Kudenov, Michael W.

2017-05-01

This paper presents a reconstruction algorithm for the Spatial-Spectral Multiplexing (SSM) optical system. The goal of this algorithm is to recover the three-dimensional spatial and spectral information of a scene, given that a one-dimensional spectrometer array is used to sample the pupil of the spatial-spectral modulator. The challenge of the reconstruction is that the non-parametric representation of the three-dimensional spatial and spectral object requires a large number of variables, thus leading to an underdetermined linear system that is hard to uniquely recover. We propose to reparameterize the spectrum using B-spline functions to reduce the number of unknown variables. Our reconstruction algorithm then solves the improved linear system via a least- square optimization of such B-spline coefficients with additional spatial smoothness regularization. The ground truth object and the optical model for the measurement matrix are simulated with both spatial and spectral assumptions according to a realistic field of view. In order to test the robustness of the algorithm, we add Poisson noise to the measurement and test on both two-dimensional and three-dimensional spatial and spectral scenes. Our analysis shows that the root mean square error of the recovered results can be achieved within 5.15%.

Classification Objects, Ideal Observers & Generative Models

ERIC Educational Resources Information Center

Olman, Cheryl; Kersten, Daniel

2004-01-01

A successful vision system must solve the problem of deriving geometrical information about three-dimensional objects from two-dimensional photometric input. The human visual system solves this problem with remarkable efficiency, and one challenge in vision research is to understand how neural representations of objects are formed and what visual…

Three-dimensional representation of curved nanowires.

PubMed

Huang, Z; Dikin, D A; Ding, W; Qiao, Y; Chen, X; Fridman, Y; Ruoff, R S

2004-12-01

Nanostructures, such as nanowires, nanotubes and nanocoils, can be described in many cases as quasi one-dimensional curved objects projecting in three-dimensional space. A parallax method to construct the correct three-dimensional geometry of such one-dimensional nanostructures is presented. A series of scanning electron microscope images was acquired at different view angles, thus providing a set of image pairs that were used to generate three-dimensional representations using a matlab program. An error analysis as a function of the view angle between the two images is presented and discussed. As an example application, the importance of knowing the true three-dimensional shape of boron nanowires is demonstrated; without the nanowire's correct length and diameter, mechanical resonance data cannot provide an accurate estimate of Young's modulus.

Image system for three dimensional, 360{degree}, time sequence surface mapping of moving objects

DOEpatents

Lu, S.Y.

1998-12-22

A three-dimensional motion camera system comprises a light projector placed between two synchronous video cameras all focused on an object-of-interest. The light projector shines a sharp pattern of vertical lines (Ronchi ruling) on the object-of-interest that appear to be bent differently to each camera by virtue of the surface shape of the object-of-interest and the relative geometry of the cameras, light projector and object-of-interest. Each video frame is captured in a computer memory and analyzed. Since the relative geometry is known and the system pre-calibrated, the unknown three-dimensional shape of the object-of-interest can be solved for by matching the intersections of the projected light lines with orthogonal epipolar lines corresponding to horizontal rows in the video camera frames. A surface reconstruction is made and displayed on a monitor screen. For 360{degree} all around coverage of the object-of-interest, two additional sets of light projectors and corresponding cameras are distributed about 120{degree} apart from one another. 20 figs.

Three-dimensional imaging of cultural heritage artifacts with holographic printers

NASA Astrophysics Data System (ADS)

Kang, Hoonjong; Stoykova, Elena; Berberova, Nataliya; Park, Jiyong; Nazarova, Dimana; Park, Joo Sup; Kim, Youngmin; Hong, Sunghee; Ivanov, Branimir; Malinowski, Nikola

2016-01-01

Holography is defined as a two-steps process of capture and reconstruction of the light wavefront scattered from three-dimensional (3D) objects. Capture of the wavefront is possible due to encoding of both amplitude and phase in the hologram as a result of interference of the light beam coming from the object and mutually coherent reference beam. Three-dimensional imaging provided by holography motivates development of digital holographic imaging methods based on computer generation of holograms as a holographic display or a holographic printer. The holographic printing technique relies on combining digital 3D object representation and encoding of the holographic data with recording of analog white light viewable reflection holograms. The paper considers 3D contents generation for a holographic stereogram printer and a wavefront printer as a means of analogue recording of specific artifacts which are complicated objects with regards to conventional analog holography restrictions.

High-resolution ab initio three-dimensional x-ray diffraction microscopy

DOE PAGES

Chapman, Henry N.; Barty, Anton; Marchesini, Stefano; ...

2006-01-01

Coherent x-ray diffraction microscopy is a method of imaging nonperiodic isolated objects at resolutions limited, in principle, by only the wavelength and largest scattering angles recorded. We demonstrate x-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the three-dimensional diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a nonperiodic object. We also construct two-dimensional images of thick objects with greatly increased depth of focus (without loss of transverse spatialmore » resolution). These methods can be used to image biological and materials science samples at high resolution with x-ray undulator radiation and establishes the techniques to be used in atomic-resolution ultrafast imaging at x-ray free-electron laser sources.« less

The Evolution of Photography and Three-Dimensional Imaging in Plastic Surgery.

PubMed

Weissler, Jason M; Stern, Carrie S; Schreiber, Jillian E; Amirlak, Bardia; Tepper, Oren M

2017-03-01

Throughout history, the technological advancements of conventional clinical photography in plastic surgery have not only refined the methods available to the plastic surgeon, but have invigorated the profession through technology. The technology of the once traditional two-dimensional photograph has since been revolutionized and refashioned to incorporate novel applications, which have since become the standard in clinical photography. Contrary to traditional standardized two-dimensional photographs, three-dimensional photography provides the surgeon with an invaluable volumetric and morphologic analysis by demonstrating true surface dimensions both preoperatively and postoperatively. Clinical photography has served as one of the fundamental objective means by which plastic surgeons review outcomes; however, the newer three-dimensional technology has been primarily used to enhance the preoperative consultation with surgical simulations. The authors intend to familiarize readers with the notion that three-dimensional photography extends well beyond its marketing application during surgical consultation. For the cosmetic surgeon, as the application of three-dimensional photography continues to mature in facial plastic surgery, it will continue to bypass the dated conventional photographic methods plastic surgeons once relied on. This article reviews a paradigm shift and provides a historical review of the fascinating evolution of photography in plastic surgery by highlighting the clinical utility of three-dimensional photography as an adjunct to plastic and reconstructive surgery practices. As three-dimensional photographic technology continues to evolve, its application in facial plastic surgery will provide an opportunity for a new objective standard in plastic surgery.

Social enrichment improves social recognition memory in male rats.

PubMed

Toyoshima, Michimasa; Yamada, Kazuo; Sugita, Manami; Ichitani, Yukio

2018-05-01

The social environment is thought to have a strong impact on cognitive functions. In the present study, we investigated whether social enrichment could affect rats' memory ability using the "Different Objects Task (DOT)," in which the levels of memory load could be modulated by changing the number of objects to be remembered. In addition, we applied the DOT to a social discrimination task using unfamiliar conspecific juveniles instead of objects. Animals were housed in one of the three different housing conditions after weaning [postnatal day (PND) 21]: social-separated (1 per cage), standard (3 per cage), or social-enriched (10 per cage) conditions. The object and social recognition tasks were conducted on PND 60. In the sample phase, the rats were allowed to explore a field in which 3, 4, or 5 different, unfamiliar stimuli (conspecific juveniles through a mesh or objects) were presented. In the test phase conducted after a 5-min delay, social-separated rats were able to discriminate the novel conspecific from the familiar ones only under the condition in which three different conspecifics were presented; social-enriched rats managed to recognize the novel conspecific even under the condition of five different conspecifics. On the other hand, in the object recognition task, both social-separated and social-enriched rats were able to discriminate the novel object from the familiar ones under the condition of five different objects. These results suggest that social enrichment can enhance social, but not object, memory span.

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

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

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

Ray tracing a three dimensional scene using a grid

DOEpatents

Wald, Ingo; Ize, Santiago; Parker, Steven G; Knoll, Aaron

2013-02-26

Ray tracing a three-dimensional scene using a grid. One example embodiment is a method for ray tracing a three-dimensional scene using a grid. In this example method, the three-dimensional scene is made up of objects that are spatially partitioned into a plurality of cells that make up the grid. The method includes a first act of computing a bounding frustum of a packet of rays, and a second act of traversing the grid slice by slice along a major traversal axis. Each slice traversal includes a first act of determining one or more cells in the slice that are overlapped by the frustum and a second act of testing the rays in the packet for intersection with any objects at least partially bounded by the one or more cells overlapped by the frustum.

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

PubMed Central

Kuwabara, Megumi; Smith, Linda B.

2016-01-01

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

Multiple mechanisms underlie defective recognition of melanoma cells cultured in three-dimensional architectures by antigen-specific cytotoxic T lymphocytes

PubMed Central

Feder-Mengus, C; Ghosh, S; Weber, W P; Wyler, S; Zajac, P; Terracciano, L; Oertli, D; Heberer, M; Martin, I; Spagnoli, G C; Reschner, A

2007-01-01

Cancer cells' growth in three-dimensional (3D) architectures promotes resistance to drugs, cytokines, or irradiation. We investigated effects of 3D culture as compared to monolayers (2D) on melanoma cells' recognition by tumour-associated antigen (TAA)-specific HLA-A*0201-restricted cytotoxic T-lymphocytes (CTL). Culture of HBL, D10 (both HLA-A*0201+, TAA+) and NA8 (HLA-A*0201+, TAA−) melanoma cells on polyHEMA-coated plates, resulted in generation of 3D multicellular tumour spheroids (MCTS). Interferon-gamma (IFN-γ) production by HLA-A*0201-restricted Melan-A/MART-127–35 or gp100280–288-specific CTL clones served as immunorecognition marker. Co-culture with melanoma MCTS, resulted in defective TAA recognition by CTL as compared to 2D as witnessed by decreased IFN-γ production and decreased Fas Ligand, perforin and granzyme B gene expression. A multiplicity of mechanisms were potentially involved. First, MCTS per se limit CTL capacity of recognising HLA class I restricted antigens by reducing exposed cell surfaces. Second, expression of melanoma differentiation antigens is downregulated in MCTS. Third, expression of HLA class I molecules can be downregulated in melanoma MCTS, possibly due to decreased interferon-regulating factor-1 gene expression. Fourth, lactic acid production is increased in MCTS, as compared to 2D. These data suggest that melanoma cells growing in 3D, even in the absence of immune selection, feature characteristics capable of dramatically inhibiting TAA recognition by specific CTL. PMID:17342088

Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

PubMed

Moghadam, Saeed Montazeri; Seyyedsalehi, Seyyed Ali

2018-05-31

Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthesize and interpolate new and imaginary data. This synthesis is possibly a simple model of imaginations in human brain where the components are expressed in a nonlinear low dimensional manifold. The current paper introduces a novel Dynamic Deep Bottleneck Neural Network to analyze and extract three main features of videos regarding the expression of emotions on the face. These main features are identity, emotion and expression intensity that are laid in three different sub-manifolds of one nonlinear general manifold. The proposed model enjoying the advantages of recurrent networks was used to analyze the sequence and dynamics of information in videos. It is noteworthy to mention that this model also has also the potential to synthesize new videos showing variations of one specific emotion on the face of unknown subjects. Experiments on discrimination and recognition ability of extracted components showed that the proposed model has an average of 97.77% accuracy in recognition of six prominent emotions (Fear, Surprise, Sadness, Anger, Disgust, and Happiness), and 78.17% accuracy in the recognition of intensity. The produced videos revealed variations from neutral to the apex of an emotion on the face of the unfamiliar test subject which is on average 0.8 similar to reference videos in the scale of the SSIM method. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Rapid prototyping: a very promising method].

PubMed

Haverman, T M; Karagozoglu, K H; Prins, H-J; Schulten, E A J M; Forouzanfar, T

2013-03-01

Rapid prototyping is a method which makes it possible to produce a three-dimensional model based on two-dimensional imaging. Various rapid prototyping methods are available for modelling, such as stereolithography, selective laser sintering, direct laser metal sintering, two-photon polymerization, laminated object manufacturing, three-dimensional printing, three-dimensional plotting, polyjet inkjet technology,fused deposition modelling, vacuum casting and milling. The various methods currently being used in the biomedical sector differ in production, materials and properties of the three-dimensional model which is produced. Rapid prototyping is mainly usedforpreoperative planning, simulation, education, and research into and development of bioengineering possibilities.

The effect of soluble uterine factors on porcine embryo development within a three-dimensional alginate matrix system

USDA-ARS?s Scientific Manuscript database

Between day 10 and 12 of gestation in the pig, the embryo undergoes a dramatic morphological change, known as elongation. During elongation the embryo produces and secretes estrogen, which serves as a key signal for maternal recognition of pregnancy. The uterine environment prepares for embryo elong...

Automatic target recognition apparatus and method

DOEpatents

Baumgart, Chris W.; Ciarcia, Christopher A.

2000-01-01

An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

Object-Place Recognition Learning Triggers Rapid Induction of Plasticity-Related Immediate Early Genes and Synaptic Proteins in the Rat Dentate Gyrus

PubMed Central

Soulé, Jonathan; Penke, Zsuzsa; Kanhema, Tambudzai; Alme, Maria Nordheim; Laroche, Serge; Bramham, Clive R.

2008-01-01

Long-term recognition memory requires protein synthesis, but little is known about the coordinate regulation of specific genes. Here, we examined expression of the plasticity-associated immediate early genes (Arc, Zif268, and Narp) in the dentate gyrus following long-term object-place recognition learning in rats. RT-PCR analysis from dentate gyrus tissue collected shortly after training did not reveal learning-specific changes in Arc mRNA expression. In situ hybridization and immunohistochemistry were therefore used to assess possible sparse effects on gene expression. Learning about objects increased the density of granule cells expressing Arc, and to a lesser extent Narp, specifically in the dorsal blade of the dentate gyrus, while Zif268 expression was elevated across both blades. Thus, object-place recognition triggers rapid, blade-specific upregulation of plasticity-associated immediate early genes. Furthermore, Western blot analysis of dentate gyrus homogenates demonstrated concomitant upregulation of three postsynaptic density proteins (Arc, PSD-95, and α-CaMKII) with key roles in long-term synaptic plasticity and long-term memory. PMID:19190776

Computational techniques to enable visualizing shapes of objects of extra spatial dimensions

NASA Astrophysics Data System (ADS)

Black, Don Vaughn, II

Envisioning extra dimensions beyond the three of common experience is a daunting challenge for three dimensional observers. Intuition relies on experience gained in a three dimensional environment. Gaining experience with virtual four dimensional objects and virtual three manifolds in four-space on a personal computer may provide the basis for an intuitive grasp of four dimensions. In order to enable such a capability for ourselves, it is first necessary to devise and implement a computationally tractable method to visualize, explore, and manipulate objects of dimension beyond three on the personal computer. A technology is described in this dissertation to convert a representation of higher dimensional models into a format that may be displayed in realtime on graphics cards available on many off-the-shelf personal computers. As a result, an opportunity has been created to experience the shape of four dimensional objects on the desktop computer. The ultimate goal has been to provide the user a tangible and memorable experience with mathematical models of four dimensional objects such that the user can see the model from any user selected vantage point. By use of a 4D GUI, an arbitrary convex hull or 3D silhouette of the 4D model can be rotated, panned, scrolled, and zoomed until a suitable dimensionally reduced view or Aspect is obtained. The 4D GUI then allows the user to manipulate a 3-flat hyperplane cutting tool to slice the model at an arbitrary orientation and position to extract or "pluck" an embedded 3D slice or "aspect" from the embedding four-space. This plucked 3D aspect can be viewed from all angles via a conventional 3D viewer using three multiple POV viewports, and optionally exported to a third party CAD viewer for further manipulation. Plucking and Manipulating the Aspect provides a tangible experience for the end-user in the same manner as any 3D Computer Aided Design viewing and manipulation tool does for the engineer or a 3D video game provides for the nascent student.

A global optimization algorithm for protein surface alignment

PubMed Central

2010-01-01

Background A relevant problem in drug design is the comparison and recognition of protein binding sites. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site since the conformation, size and chemical composition of the protein surface are all relevant for the interaction with a specific ligand. Several matching strategies have been designed for the recognition of protein-ligand binding sites and of protein-protein interfaces but the problem cannot be considered solved. Results In this paper we propose a new method for local structural alignment of protein surfaces based on continuous global optimization techniques. Given the three-dimensional structures of two proteins, the method finds the isometric transformation (rotation plus translation) that best superimposes active regions of two structures. We draw our inspiration from the well-known Iterative Closest Point (ICP) method for three-dimensional (3D) shapes registration. Our main contribution is in the adoption of a controlled random search as a more efficient global optimization approach along with a new dissimilarity measure. The reported computational experience and comparison show viability of the proposed approach. Conclusions Our method performs well to detect similarity in binding sites when this in fact exists. In the future we plan to do a more comprehensive evaluation of the method by considering large datasets of non-redundant proteins and applying a clustering technique to the results of all comparisons to classify binding sites. PMID:20920230

Systems in Development: Motor Skill Acquisition Facilitates Three-Dimensional Object Completion

ERIC Educational Resources Information Center

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

2010-01-01

How do infants learn to perceive the backs of objects that they see only from a limited viewpoint? Infants' 3-dimensional object completion abilities emerge in conjunction with developing motor skills--independent sitting and visual-manual exploration. Infants at 4.5 to 7.5 months of age (n = 28) were habituated to a limited-view object and tested…

Transmission mode terahertz computed tomography

DOEpatents

Ferguson, Bradley Stuart; Wang, Shaohong; Zhang, Xi-Cheng

2006-10-10

A method of obtaining a series of images of a three-dimensional object by transmitting pulsed terahertz (THz) radiation through the entire object from a plurality of angles, optically detecting changes in the transmitted THz radiation using pulsed laser radiation, and constructing a plurality of imaged slices of the three-dimensional object using the detected changes in the transmitted THz radiation. The THz radiation is transmitted through the object as a scanning spot. The object is placed within the Rayleigh range of the focused THz beam and a focusing system is used to transfer the imaging plane from adjacent the object to a desired distance away from the object. A related system is also disclosed.

Patterns of Visual Attention to Faces and Objects in Autism Spectrum Disorder

ERIC Educational Resources Information Center

McPartland, James C.; Webb, Sara Jane; Keehn, Brandon; Dawson, Geraldine

2011-01-01

This study used eye-tracking to examine visual attention to faces and objects in adolescents with autism spectrum disorder (ASD) and typical peers. Point of gaze was recorded during passive viewing of images of human faces, inverted human faces, monkey faces, three-dimensional curvilinear objects, and two-dimensional geometric patterns.…

A Three-Dimensional Object Orientation Detector Assisting People with Developmental Disabilities to Control Their Environmental Stimulation through Simple Occupational Activities with a Nintendo Wii Remote Controller

ERIC Educational Resources Information Center

Shih, Ching-Hsiang; Chang, Man-Ling; Mohua, Zhang

2012-01-01

This study evaluated whether two people with developmental disabilities would be able to actively perform simple occupational activities to control their preferred environmental stimulation using a Nintendo Wii Remote Controller with a newly developed three-dimensional object orientation detection program (TDOODP, i.e. a new software program,…

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

PubMed

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

2009-02-01

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

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

PubMed Central

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

2009-01-01

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

How Students Solve Problems in Spatial Geometry while Using a Software Application for Visualizing 3D Geometric Objects

ERIC Educational Resources Information Center

Widder, Mirela; Gorsky, Paul

2013-01-01

In schools, learning spatial geometry is usually dependent upon a student's ability to visualize three dimensional geometric configurations from two dimensional drawings. Such a process, however, often creates visual obstacles which are unique to spatial geometry. Useful software programs which realistically depict three dimensional geometric…

Three-dimensional facial recognition using passive long-wavelength infrared polarimetric imaging.

PubMed

Yuffa, Alex J; Gurton, Kristan P; Videen, Gorden

2014-12-20

We use a polarimetric camera to record the Stokes parameters and the degree of linear polarization of long-wavelength infrared radiation emitted by human faces. These Stokes images are combined with Fresnel relations to extract the surface normal at each pixel. Integrating over these surface normals yields a three-dimensional facial image. One major difficulty of this technique is that the normal vectors determined from the polarizations are not unique. We overcome this problem by introducing an additional boundary condition on the subject. The major sources of error in producing inversions are noise in the images caused by scattering of the background signal and the ambiguity in determining the surface normals from the Fresnel coefficients.

Image system for three dimensional, 360 DEGREE, time sequence surface mapping of moving objects

DOEpatents

Lu, Shin-Yee

1998-01-01

A three-dimensional motion camera system comprises a light projector placed between two synchronous video cameras all focused on an object-of-interest. The light projector shines a sharp pattern of vertical lines (Ronchi ruling) on the object-of-interest that appear to be bent differently to each camera by virtue of the surface shape of the object-of-interest and the relative geometry of the cameras, light projector and object-of-interest Each video frame is captured in a computer memory and analyzed. Since the relative geometry is known and the system pre-calibrated, the unknown three-dimensional shape of the object-of-interest can be solved for by matching the intersections of the projected light lines with orthogonal epipolar lines corresponding to horizontal rows in the video camera frames. A surface reconstruction is made and displayed on a monitor screen. For 360.degree. all around coverage of theobject-of-interest, two additional sets of light projectors and corresponding cameras are distributed about 120.degree. apart from one another.

The holographic display of three-dimensional medical objects through the usage of a shiftable cylindrical lens

NASA Astrophysics Data System (ADS)

Teng, Dongdong; Liu, Lilin; Zhang, Yueli; Pang, Zhiyong; Wang, Biao

2014-09-01

Through the creative usage of a shiftable cylindrical lens, a wide-view-angle holographic display system is developed for medical object display in real three-dimensional (3D) space based on a time-multiplexing method. The two-dimensional (2D) source images for all computer generated holograms (CGHs) needed by the display system are only one group of computerized tomography (CT) or magnetic resonance imaging (MRI) slices from the scanning device. Complicated 3D message reconstruction on the computer is not necessary. A pelvis is taken as the target medical object to demonstrate this method and the obtained horizontal viewing angle reaches 28°.

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 a low-cost, low-computation system for real-time object recognition tasks on mobile robots. This system differs from all previous approaches in that it is relatively simple, robust, fast, and inexpensive.

LANDMARK-BASED SPEECH RECOGNITION: REPORT OF THE 2004 JOHNS HOPKINS SUMMER WORKSHOP.

PubMed

Hasegawa-Johnson, Mark; Baker, James; Borys, Sarah; Chen, Ken; Coogan, Emily; Greenberg, Steven; Juneja, Amit; Kirchhoff, Katrin; Livescu, Karen; Mohan, Srividya; Muller, Jennifer; Sonmez, Kemal; Wang, Tianyu

2005-01-01

Three research prototype speech recognition systems are described, all of which use recently developed methods from artificial intelligence (specifically support vector machines, dynamic Bayesian networks, and maximum entropy classification) in order to implement, in the form of an automatic speech recognizer, current theories of human speech perception and phonology (specifically landmark-based speech perception, nonlinear phonology, and articulatory phonology). All three systems begin with a high-dimensional multiframe acoustic-to-distinctive feature transformation, implemented using support vector machines trained to detect and classify acoustic phonetic landmarks. Distinctive feature probabilities estimated by the support vector machines are then integrated using one of three pronunciation models: a dynamic programming algorithm that assumes canonical pronunciation of each word, a dynamic Bayesian network implementation of articulatory phonology, or a discriminative pronunciation model trained using the methods of maximum entropy classification. Log probability scores computed by these models are then combined, using log-linear combination, with other word scores available in the lattice output of a first-pass recognizer, and the resulting combination score is used to compute a second-pass speech recognition output.

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

PubMed Central

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

A color-coded vision scheme for robotics

NASA Technical Reports Server (NTRS)

Johnson, Kelley Tina

1991-01-01

Most vision systems for robotic applications rely entirely on the extraction of information from gray-level images. Humans, however, regularly depend on color to discriminate between objects. Therefore, the inclusion of color in a robot vision system seems a natural extension of the existing gray-level capabilities. A method for robot object recognition using a color-coding classification scheme is discussed. The scheme is based on an algebraic system in which a two-dimensional color image is represented as a polynomial of two variables. The system is then used to find the color contour of objects. In a controlled environment, such as that of the in-orbit space station, a particular class of objects can thus be quickly recognized by its color.

Direct discriminant locality preserving projection with Hammerstein polynomial expansion.

PubMed

Chen, Xi; Zhang, Jiashu; Li, Defang

2012-12-01

Discriminant locality preserving projection (DLPP) is a linear approach that encodes discriminant information into the objective of locality preserving projection and improves its classification ability. To enhance the nonlinear description ability of DLPP, we can optimize the objective function of DLPP in reproducing kernel Hilbert space to form a kernel-based discriminant locality preserving projection (KDLPP). However, KDLPP suffers the following problems: 1) larger computational burden; 2) no explicit mapping functions in KDLPP, which results in more computational burden when projecting a new sample into the low-dimensional subspace; and 3) KDLPP cannot obtain optimal discriminant vectors, which exceedingly optimize the objective of DLPP. To overcome the weaknesses of KDLPP, in this paper, a direct discriminant locality preserving projection with Hammerstein polynomial expansion (HPDDLPP) is proposed. The proposed HPDDLPP directly implements the objective of DLPP in high-dimensional second-order Hammerstein polynomial space without matrix inverse, which extracts the optimal discriminant vectors for DLPP without larger computational burden. Compared with some other related classical methods, experimental results for face and palmprint recognition problems indicate the effectiveness of the proposed HPDDLPP.

New technique for real-time distortion-invariant multiobject recognition and classification

NASA Astrophysics Data System (ADS)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

3D interactive augmented reality-enhanced digital learning systems for mobile devices

NASA Astrophysics Data System (ADS)

Feng, Kai-Ten; Tseng, Po-Hsuan; Chiu, Pei-Shuan; Yang, Jia-Lin; Chiu, Chun-Jie

2013-03-01

With enhanced processing capability of mobile platforms, augmented reality (AR) has been considered a promising technology for achieving enhanced user experiences (UX). Augmented reality is to impose virtual information, e.g., videos and images, onto a live-view digital display. UX on real-world environment via the display can be e ectively enhanced with the adoption of interactive AR technology. Enhancement on UX can be bene cial for digital learning systems. There are existing research works based on AR targeting for the design of e-learning systems. However, none of these work focuses on providing three-dimensional (3-D) object modeling for en- hanced UX based on interactive AR techniques. In this paper, the 3-D interactive augmented reality-enhanced learning (IARL) systems will be proposed to provide enhanced UX for digital learning. The proposed IARL systems consist of two major components, including the markerless pattern recognition (MPR) for 3-D models and velocity-based object tracking (VOT) algorithms. Realistic implementation of proposed IARL system is conducted on Android-based mobile platforms. UX on digital learning can be greatly improved with the adoption of proposed IARL systems.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-01-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Astrophysics Data System (ADS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-02-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

Learning discriminative features from RGB-D images for gender and ethnicity identification

NASA Astrophysics Data System (ADS)

Azzakhnini, Safaa; Ballihi, Lahoucine; Aboutajdine, Driss

2016-11-01

The development of sophisticated sensor technologies gave rise to an interesting variety of data. With the appearance of affordable devices, such as the Microsoft Kinect, depth-maps and three-dimensional data became easily accessible. This attracted many computer vision researchers seeking to exploit this information in classification and recognition tasks. In this work, the problem of face classification in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition and ethnicity classification to understand how much depth data can improve the quality of recognition. Furthermore, we investigate which combination of face descriptors, feature selection methods, and learning techniques is best suited to better exploit RGB-D images. The experimental results show that depth data improve the recognition accuracy for gender and ethnicity classification applications in many use cases.

Geometrical structure of Neural Networks: Geodesics, Jeffrey's Prior and Hyper-ribbons

NASA Astrophysics Data System (ADS)

Hayden, Lorien; Alemi, Alex; Sethna, James

2014-03-01

Neural networks are learning algorithms which are employed in a host of Machine Learning problems including speech recognition, object classification and data mining. In practice, neural networks learn a low dimensional representation of high dimensional data and define a model manifold which is an embedding of this low dimensional structure in the higher dimensional space. In this work, we explore the geometrical structure of a neural network model manifold. A Stacked Denoising Autoencoder and a Deep Belief Network are trained on handwritten digits from the MNIST database. Construction of geodesics along the surface and of slices taken from the high dimensional manifolds reveal a hierarchy of widths corresponding to a hyper-ribbon structure. This property indicates that neural networks fall into the class of sloppy models, in which certain parameter combinations dominate the behavior. Employing this information could prove valuable in designing both neural network architectures and training algorithms. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No . DGE-1144153.

Fragility of haptic memory in human full-term newborns.

PubMed

Lejeune, Fleur; Borradori Tolsa, Cristina; Gentaz, Edouard; Barisnikov, Koviljka

2018-05-31

Numerous studies have established that newborns can memorize tactile information about the specific features of an object with their hands and detect differences with another object. However, the robustness of haptic memory abilities has already been examined in preterm newborns and in full-term infants, but not yet in full-term newborns. This research is aimed to better understand the robustness of haptic memory abilities at birth by examining the effects of a change in the objects' temperature and haptic interference. Sixty-eight full-term newborns (mean postnatal age: 2.5 days) were included. The two experiments were conducted in three phases: habituation (repeated presentation of the same object, a prism or cylinder in the newborn's hand), discrimination (presentation of a novel object), and recognition (presentation of the familiar object). In Experiment 1, the change in the objects' temperature was controlled during the three phases. Results reveal that newborns can memorize specific features that differentiate prism and cylinder shapes by touch, and discriminate between them, but surprisingly they did not show evidence of recognizing them after interference. As no significant effect of the temperature condition was observed in habituation, discrimination and recognition abilities, these findings suggest that discrimination abilities in newborns may be determined by the detection of shape differences. Overall, it seems that the ontogenesis of haptic recognition memory is not linear. The developmental schedule is likely crucial for haptic development between 34 and 40 GW. Copyright © 2018 Elsevier Inc. All rights reserved.

SABRINA: an interactive three-dimensional geometry-mnodeling program for MCNP

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

West, J.T. III

SABRINA is a fully interactive three-dimensional geometry-modeling program for MCNP, a Los Alamos Monte Carlo code for neutron and photon transport. In SABRINA, a user constructs either body geometry or surface geometry models and debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo analysis. 2 refs., 33 figs.

The Joint Role of Trained, Untrained, and Observed Actions at the Origins of Goal Recognition

PubMed Central

Gerson, Sarah A.; Woodward, Amanda L.

2014-01-01

Recent findings across a variety of domains reveal the benefits of self-produced experience on object exploration, object knowledge, attention, and action perception. The influence of active experience may be particularly important in infancy, when motor development is undergoing great changes. Despite the importance of self-produced experience, we know that infants and young children are eventually able to gain knowledge through purely observational experience. In the current work, three-month-old infants were given experience with object-directed actions in one of three forms and their recognition of the goal of grasping actions was then assessed in a habituation paradigm. All infants were given the chance to manually interact with the toys without assistance (a difficult task for most three-month-olds). Two of the three groups were then given additional experience with object-directed actions, either through active training (in which Velcro mittens helped infants act more efficiently) or observational training. Findings support the conclusion that self-produced experience is uniquely informative for action perception and suggest that individual differences in spontaneous motor activity may interact with observational experience to inform action perception early in life. PMID:24468646

An unconventional depiction of viewpoint in rock art.

PubMed

Pettigrew, Jack; Scott-Virtue, Lee

2015-01-01

Rock art in Africa sometimes takes advantage of three-dimensional features of the rock wall, such as fissures or protuberances, that can be incorporated into the artistic composition (Lewis-Williams, 2002). More commonly, rock artists choose uniform walls on which two-dimensional depictions may represent three-dimensional figures or objects. In this report we present such a two-dimensional depiction in rock art that we think reveals an intention by the artist to represent an unusual three-dimensional viewpoint, namely, with the two human figures facing into the rock wall, instead of the accustomed Western viewpoint facing out!

Close range fault tolerant noncontacting position sensor

DOEpatents

Bingham, D.N.; Anderson, A.A.

1996-02-20

A method and system are disclosed for locating the three dimensional coordinates of a moving or stationary object in real time. The three dimensional coordinates of an object in half space or full space are determined based upon the time of arrival or phase of the wave front measured by a plurality of receiver elements and an established vector magnitudes proportional to the measured time of arrival or phase at each receiver element. The coordinates of the object are calculated by solving a matrix equation or a set of closed form algebraic equations. 3 figs.

SU-E-I-91: Development of a Compact Radiographic Simulator Using Microsoft Kinect.

PubMed

Ono, M; Kozono, K; Aoki, M; Mizoguchi, A; Kamikawa, Y; Umezu, Y; Arimura, H; Toyofuku, F

2012-06-01

Radiographic simulator system is useful for learning radiographic techniques and confirmation of positioning before x-ray irradiation. Conventional x-ray simulators have drawbacks in cost and size, and are only applicable to situations in which position of the object does not change. Therefore, we have developed a new radiographic simulator system using an infrared-ray based three-dimensional shape measurement device (Microsoft Kinect). We made a computer program using OpenCV and OpenNI for processing of depth image data obtained from Kinect, and calculated the exact distance from Kinect to the object by calibration. Theobject was measured from various directions, and positional relationship between the x-ray tube and the object was obtained. X-ray projection images were calculated by projecting x-rays onto the mathematical three-dimensional CT data of a head phantom with almost the same size. The object was rotated from 0 degree (standard position) through 90 degrees in increments of 10 degrees, and the accuracy of the measured rotation angle values was evaluated. In order to improve the computational time, the projection image size was changed (512*512, 256*256, and 128*128). The x-ray simulation images corresponding to the radiographic images produced by using the x-ray tube were obtained. The three-dimensional position of the object was measured with good precision from 0 to 50 degrees, but above 50 degrees, measured position error increased with the increase of the rotation angle. The computational time and image size were 30, 12, and 7 seconds for 512*512, 256*256, and 128*128, respectively. We could measure the three-dimensional position of the object using properly calibrated Kinect sensor, and obtained projection images at relatively high-speed using the three-dimensional CTdata. It was suggested that this system can be used for obtaining simulated projection x-ray images before x-ray exposure by attaching this device onto an x-ray tube. © 2012 American Association of Physicists in Medicine.

The Coupling of Finite Element and Integral Equation Representations for Efficient Three-Dimensional Modeling of Electromagnetic Scattering and Radiation

NASA Technical Reports Server (NTRS)

Cwik, Tom; Zuffada, Cinzia; Jamnejad, Vahraz

1996-01-01

Finite element modeling has proven useful for accurtely simulating scattered or radiated fields from complex three-dimensional objects whose geometry varies on the scale of a fraction of a wavelength.

Application of 3D Zernike descriptors to shape-based ligand similarity searching.

PubMed

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Application of 3D Zernike descriptors to shape-based ligand similarity searching

PubMed Central

2009-01-01

Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD. PMID:20150998

Toward three-dimensional microelectronic systems: directed self-assembly of silicon microcubes via DNA surface functionalization.

PubMed

Lämmerhardt, Nico; Merzsch, Stephan; Ledig, Johannes; Bora, Achyut; Waag, Andreas; Tornow, Marc; Mischnick, Petra

2013-07-02

The huge and intelligent processing power of three-dimensional (3D) biological "processors" like the human brain with clock speeds of only 0.1 kHz is an extremely fascinating property, which is based on a massively parallel interconnect strategy. Artificial silicon microprocessors are 7 orders of magnitude faster. Nevertheless, they do not show any indication of intelligent processing power, mostly due to their very limited interconnectivity. Massively parallel interconnectivity can only be realized in three dimensions. Three-dimensional artificial processors would therefore be at the root of fabricating artificially intelligent systems. A first step in this direction would be the self-assembly of silicon based building blocks into 3D structures. We report on the self-assembly of such building blocks by molecular recognition, and on the electrical characterization of the formed assemblies. First, planar silicon substrates were functionalized with self-assembling monolayers of 3-aminopropyltrimethoxysilane for coupling of oligonucleotides (single stranded DNA) with glutaric aldehyde. The oligonucleotide immobilization was confirmed and quantified by hybridization with fluorescence-labeled complementary oligonucleotides. After the individual processing steps, the samples were analyzed by contact angle measurements, ellipsometry, atomic force microscopy, and fluorescence microscopy. Patterned DNA-functionalized layers were fabricated by microcontact printing (μCP) and photolithography. Silicon microcubes of 3 μm edge length as model objects for first 3D self-assembly experiments were fabricated out of silicon-on-insulator (SOI) wafers by a combination of reactive ion etching (RIE) and selective wet etching. The microcubes were then surface-functionalized using the same protocol as on planar substrates, and their self-assembly was demonstrated both on patterned silicon surfaces (88% correctly placed cubes), and to cube aggregates by complementary DNA functionalization and hybridization. The yield of formed aggregates was found to be about 44%, with a relative fraction of dimers of some 30%. Finally, the electrical properties of the formed dimers were characterized using probe tips inside a scanning electron microscope.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

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

PubMed

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

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual recognition. Copyright © 2010 Elsevier Srl. All rights reserved.

Exploratory behavior and recognition memory in medial septal electrolytic, neuro- and immunotoxic lesioned rats.

PubMed

Dashniani, M G; Burjanadze, M A; Naneishvili, T L; Chkhikvishvili, N C; Beselia, G V; Kruashvili, L B; Pochkhidze, N O; Chighladze, M R

2015-01-01

In the present study, the effect of the medial septal (MS) lesions on exploratory activity in the open field and the spatial and object recognition memory has been investigated. This experiment compares three types of MS lesions: electrolytic lesions that destroy cells and fibers of passage, neurotoxic - ibotenic acid lesions that spare fibers of passage but predominantly affect the septal noncholinergic neurons, and immunotoxin - 192 IgG-saporin infusions that only eliminate cholinergic neurons. The main results are: the MS electrolytic lesioned rats were impaired in habituating to the environment in the repeated spatial environment, but rats with immuno- or neurotoxic lesions of the MS did not differ from control ones; the MS electrolytic and ibotenic acid lesioned rats showed an increase in their exploratory activity to the objects and were impaired in habituating to the objects in the repeated spatial environment; rats with immunolesions of the MS did not differ from control rats; electrolytic lesions of the MS disrupt spatial recognition memory; rats with immuno- or neurotoxic lesions of the MS were normal in detecting spatial novelty; all of the MS-lesioned and control rats clearly reacted to the object novelty by exploring the new object more than familiar ones. Results observed across lesion techniques indicate that: (i) the deficits after nonselective damage of MS are limited to a subset of cognitive processes dependent on the hippocampus, (ii) MS is substantial for spatial, but not for object recognition memory - the object recognition memory can be supported outside the septohippocampal system; (iii) the selective loss of septohippocampal cholinergic or noncholinergic projections does not disrupt the function of the hippocampus to a sufficient extent to impair spatial recognition memory; (iv) there is dissociation between the two major components (cholinergic and noncholinergic) of the septohippocampal pathway in exploratory behavior assessed in the open field - the memory exhibited by decrements in exploration of repeated object presentations is affected by either electrolytic or ibotenic lesions, but not saporin.

A three-dimensional object orientation detector assisting people with developmental disabilities to control their environmental stimulation through simple occupational activities with a Nintendo Wii Remote Controller.

PubMed

Shih, Ching-Hsiang; Chang, Man-Ling; Mohua, Zhang

2012-01-01

This study evaluated whether two people with developmental disabilities would be able to actively perform simple occupational activities to control their preferred environmental stimulation using a Nintendo Wii Remote Controller with a newly developed three-dimensional object orientation detection program (TDOODP, i.e. a new software program, which turns a Wii Remote Controller into a three-dimensional object orientation detector). An ABAB design, in which A represented the baseline and B represented intervention phases, was adopted in this study. The data shows that the performance of both participants has significantly increased (i.e. they perform more simple occupational activities to activate the control system to produce environmental stimulation) during the intervention phases. The practical and developmental implications of the findings are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-03-01

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

Modern moulage: evaluating the use of 3-dimensional prosthetic mimics in a dermatology teaching program for second-year medical students.

PubMed

Garg, Amit; Haley, Heather-Lyn; Hatem, David

2010-02-01

To evaluate the effectiveness of a teaching method that uses 3-dimensional (3D) silicone-based prosthetic mimics of common serious lesions and eruptions and to compare learning outcomes with those achieved through the conventional method of lectures with 2-dimensional (2D) images. Prospective and comparative. University of Massachusetts Medical School. Ninety second-year medical students. A 1-hour teaching intervention using a lecture with 2D images (2D group) or using 3D prosthetic mimics of lesions and eruptions (3D group). Mean scores in the domains of morphology, lesion and rash recognition, lesion and rash management, and overall performance assessed at baseline, immediately after, and 3 months after each group's respective teaching intervention. Immediately after the teaching intervention, the 3D group had significantly higher mean percentage scores than did the 2D group for overall performance (71 vs 65, P = .03), lesion recognition (65 vs 56, P = .02), and rash management (80 vs 67, P = .01). Three months later, the 3D group still had significantly higher mean percentage scores than did the 2D group for lesion recognition (47 vs 40, P = .03). The 3D group better recognized lesions at 3 months compared with at baseline, whereas the 2D group was no better at recognizing lesions at 3 months compared with at baseline. Despite limited curricular time, the novel teaching method using 3D prosthetic mimics of lesions and eruptions improves immediate and long-term learning outcomes, in particular, lesion recognition. It is also a preferred teaching format among second-year medical students.

Crack Modelling for Radiography

NASA Astrophysics Data System (ADS)

Chady, T.; Napierała, L.

2010-02-01

In this paper, possibility of creation of three-dimensional crack models, both random type and based on real-life radiographic images is discussed. Method for storing cracks in a number of two-dimensional matrices, as well algorithm for their reconstruction into three-dimensional objects is presented. Also the possibility of using iterative algorithm for matching simulated images of cracks to real-life radiographic images is discussed.

Three-dimensional propagation in near-field tomographic X-ray phase retrieval

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

Ruhlandt, Aike, E-mail: aruhlan@gwdg.de; Salditt, Tim

An extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions is presented, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. This paper presents an extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. The approach is based on a novel three-dimensional propagator and is derived for the case of optically weak objects. It can be easily implemented in current phase retrieval architectures, is computationally efficient and reduces the need for restrictive prior assumptions, resultingmore » in superior reconstruction quality.« less

Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks.

PubMed

Naz, Saeeda; Umar, Arif Iqbal; Ahmed, Riaz; Razzak, Muhammad Imran; Rashid, Sheikh Faisal; Shafait, Faisal

2016-01-01

The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult due to its Nasta'liq writing style. Nasta'liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping of characters. Therefore, the work done for recognition of Arabic script cannot be directly applied to Urdu recognition. We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta'liq writing style. Experiments show that MDLSTM attained a recognition accuracy of 98% for the unconstrained Urdu Nasta'liq printed text, which significantly outperforms the state-of-the-art techniques.

Three-Dimensional Printing Using a Photoinitiated Polymer

ERIC Educational Resources Information Center

Muskin, Joseph; Ragusa, Matthew; Gelsthorpe, Thomas

2010-01-01

Printers capable of producing three-dimensional objects are becoming more common. Most of these printers are impractical for use in the chemistry classroom because of the expense incurred in fabricating a print head that must be controlled in three dimensions. We propose a simpler solution to this problem that allows the emerging technology of…

Laser electro-optic system for rapid three-dimensional /3-D/ topographic mapping of surfaces

NASA Technical Reports Server (NTRS)

Altschuler, M. D.; Altschuler, B. R.; Taboada, J.

1981-01-01

It is pointed out that the generic utility of a robot in a factory/assembly environment could be substantially enhanced by providing a vision capability to the robot. A standard videocamera for robot vision provides a two-dimensional image which contains insufficient information for a detailed three-dimensional reconstruction of an object. Approaches which supply the additional information needed for the three-dimensional mapping of objects with complex surface shapes are briefly considered and a description is presented of a laser-based system which can provide three-dimensional vision to a robot. The system consists of a laser beam array generator, an optical image recorder, and software for controlling the required operations. The projection of a laser beam array onto a surface produces a dot pattern image which is viewed from one or more suitable perspectives. Attention is given to the mathematical method employed, the space coding technique, the approaches used for obtaining the transformation parameters, the optics for laser beam array generation, the hardware for beam array coding, and aspects of image acquisition.

US: A Cultural Mosaic Program. Groups: Alike and Different. A Social Studies Unit for Level 2 (Grades 2, 1-2, 1-2-3).

ERIC Educational Resources Information Center

Martinez, Jimmie; And Others

This curriculum guide emphasizes a multicultural approach to the teaching of social studies in grades one through three. The guide is organized around three principal objectives. The first objective is for children to describe how cultural heritage is transmitted through the recognition of special days. Lesson plans presented under this objective…

Three-to Four-Year-Olds' Recognition That Symbols Have a Stable Meaning: Pictures Are Understood Before Written Words

ERIC Educational Resources Information Center

Apperly, Ian. A.; Williams, Emily; Williams, Joelle

2004-01-01

In 4 experiments 120 three-to four-year-old non readers were asked the identity of a symbolic representation as it appeared with different objects. Consistent with Bialystok (2000), many children judged the identity of written words to vary according to the object with which they appeared but few made such errors with recognizable pictures.…

SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

PubMed Central

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

2013-01-01

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

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

NASA Astrophysics Data System (ADS)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous, similar approaches are: 1) Progressive Automated Invariant Model Generation, 2) Invariant Minimal Complete Description Set for computational efficiency, 3) Arbitrary Model Precision for robust object description and identification.

A web service system supporting three-dimensional post-processing of medical images based on WADO protocol.

PubMed

He, Longjun; Xu, Lang; Ming, Xing; Liu, Qian

2015-02-01

Three-dimensional post-processing operations on the volume data generated by a series of CT or MR images had important significance on image reading and diagnosis. As a part of the DIOCM standard, WADO service defined how to access DICOM objects on the Web, but it didn't involve three-dimensional post-processing operations on the series images. This paper analyzed the technical features of three-dimensional post-processing operations on the volume data, and then designed and implemented a web service system for three-dimensional post-processing operations of medical images based on the WADO protocol. In order to improve the scalability of the proposed system, the business tasks and calculation operations were separated into two modules. As results, it was proved that the proposed system could support three-dimensional post-processing service of medical images for multiple clients at the same moment, which met the demand of accessing three-dimensional post-processing operations on the volume data on the web.

Partial spline models for the inclusion of tropopause and frontal boundary information in otherwise smooth two- and three-dimensional objective analysis

NASA Technical Reports Server (NTRS)

Shiau, Jyh-Jen; Wahba, Grace; Johnson, Donald R.

1986-01-01

A new method, based on partial spline models, is developed for including specified discontinuities in otherwise smooth two- and three-dimensional objective analyses. The method is appropriate for including tropopause height information in two- and three-dimensinal temperature analyses, using the O'Sullivan-Wahba physical variational method for analysis of satellite radiance data, and may in principle be used in a combined variational analysis of observed, forecast, and climate information. A numerical method for its implementation is described and a prototype two-dimensional analysis based on simulated radiosonde and tropopause height data is shown. The method may also be appropriate for other geophysical problems, such as modeling the ocean thermocline, fronts, discontinuities, etc.

The Effect of Visual-Spatial Stimulation on Emergent Readers at Risk for Specific Learning Disability in Reading

ERIC Educational Resources Information Center

Zascavage, Victoria Selden; McKenzie, Ginger Kelley; Buot, Max; Woods, Carol; Orton-Gillingham, Fellow

2012-01-01

This study compared word recognition for words written in a traditional flat font to the same words written in a three-dimensional appearing font determined to create a right hemispheric stimulation. The participants were emergent readers enrolled in Montessori schools in the United States learning to read basic CVC (consonant, vowel, consonant)…

Systems and methods that generate height map models for efficient three dimensional reconstruction from depth information

DOEpatents

Frahm, Jan-Michael; Pollefeys, Marc Andre Leon; Gallup, David Robert

2015-12-08

Methods of generating a three dimensional representation of an object in a reference plane from a depth map including distances from a reference point to pixels in an image of the object taken from a reference point. Weights are assigned to respective voxels in a three dimensional grid along rays extending from the reference point through the pixels in the image based on the distances in the depth map from the reference point to the respective pixels, and a height map including an array of height values in the reference plane is formed based on the assigned weights. An n-layer height map may be constructed by generating a probabilistic occupancy grid for the voxels and forming an n-dimensional height map comprising an array of layer height values in the reference plane based on the probabilistic occupancy grid.

Magnetic Resonance Imaging of Three-Dimensional Cervical Anatomy in the Second and Third Trimester

PubMed Central

HOUSE, Michael; BHADELIA, Rafeeque A.; MYERS, Kristin; SOCRATE, Simona

2009-01-01

OBJECTIVE Although a short cervix is known to be associated with preterm birth, the patterns of three-dimensional, anatomic changes leading to a short cervix are unknown. Our objective was to 1) construct three-dimensional anatomic models during normal pregnancy and 2) use the models to compare cervical anatomy in the second and third trimester. STUDY DESIGN A cross sectional study was performed in a population of patients referred to magnetic resonance imaging (MRI) for a fetal indication. Using magnetic resonance images for guidance, three-dimensional solid models of the following anatomic structures were constructed: amniotic cavity, uterine wall, cervical stroma, cervical mucosa and anterior vaginal wall. To compare cervical anatomy in the second and third trimester, models were matched according the size of the bony pelvis. RESULTS Fourteen patients were imaged and divided into two groups according to gestational age: 20 – 24 weeks (n=7)) and 31 – 36 weeks (n=7). Compared to the second trimester, the third trimester was associated with significant descent of the amniotic sac. (p=.02). Descent of the amniotic sac was associated with modified anatomy of the uterocervical junction. These 3-dimensional changes were associated with a cervix that appeared shorter in the third trimester. CONCLUSION We report a technique for constructing MRI-based, three-dimensional anatomic models during pregnancy. Compared to the second trimester, the third trimester is associated with three-dimensional changes in the cervix and lower uterine segment. PMID:19297070

Illusions of Space: Charting Three Dimensions

ERIC Educational Resources Information Center

Glasser, Leslie

2014-01-01

We introduce various methods which are used to depict three-dimensional objects on two-dimensional surfaces. Many of these are artistic and not conducive to exact interpretation. Instead, the scientific and engineering practices and mathematics of orthographic projection are introduced, and illustrated in an accompanying interactive Excel…

Mental Rotation with Tangible Three-Dimensional Objects: A New Measure Sensitive to Developmental Differences in 4- to 8-year-old Children

ERIC Educational Resources Information Center

Hawes, Zachary; LeFevre, Jo-Anne; Xu, Chang; Bruce, Catherine D.

2015-01-01

There is an emerging consensus that spatial thinking is fundamental to later success in math and science. The goals of this study were to design and evaluate a novel test of three-dimensional (3D) mental rotation for 4- to 8-year-old children (N?=?165) that uses tangible 3D objects. Results revealed that the measure was both valid and reliable and…

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

PubMed

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

2018-02-01

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

An optimized content-aware image retargeting method: toward expanding the perceived visual field of the high-density retinal prosthesis recipients

NASA Astrophysics Data System (ADS)

Li, Heng; Zeng, Yajie; Lu, Zhuofan; Cao, Xiaofei; Su, Xiaofan; Sui, Xiaohong; Wang, Jing; Chai, Xinyu

2018-04-01

Objective. Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients’ visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible. Approach. We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients’ perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability. Main results. Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution. Significance. The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants.

Holography of Wi-fi Radiation.

PubMed

Holl, Philipp M; Reinhard, Friedemann

2017-05-05

Wireless data transmission systems such as wi-fi or Bluetooth emit coherent light-electromagnetic waves with a precisely known amplitude and phase. Propagating in space, this radiation forms a hologram-a two-dimensional wave front encoding a three-dimensional view of all objects traversed by the light beam. Here we demonstrate a scheme to record this hologram in a phase-coherent fashion across a meter-sized imaging region. We recover three-dimensional views of objects and emitters by feeding the resulting data into digital reconstruction algorithms. Employing a digital implementation of dark-field propagation to suppress multipath reflection, we significantly enhance the quality of the resulting images. We numerically simulate the hologram of a 10-m-sized building, finding that both localization of emitters and 3D tomography of absorptive objects could be feasible by this technique.

Holography of Wi-fi Radiation

NASA Astrophysics Data System (ADS)

Holl, Philipp M.; Reinhard, Friedemann

2017-05-01

Wireless data transmission systems such as wi-fi or Bluetooth emit coherent light—electromagnetic waves with a precisely known amplitude and phase. Propagating in space, this radiation forms a hologram—a two-dimensional wave front encoding a three-dimensional view of all objects traversed by the light beam. Here we demonstrate a scheme to record this hologram in a phase-coherent fashion across a meter-sized imaging region. We recover three-dimensional views of objects and emitters by feeding the resulting data into digital reconstruction algorithms. Employing a digital implementation of dark-field propagation to suppress multipath reflection, we significantly enhance the quality of the resulting images. We numerically simulate the hologram of a 10-m-sized building, finding that both localization of emitters and 3D tomography of absorptive objects could be feasible by this technique.

Three-dimensional shape measurement system applied to superficial inspection of non-metallic pipes for the hydrocarbons transport

NASA Astrophysics Data System (ADS)

Arciniegas, Javier R.; González, Andrés. L.; Quintero, L. A.; Contreras, Carlos R.; Meneses, Jaime E.

2014-05-01

Three-dimensional shape measurement is a subject that consistently produces high scientific interest and provides information for medical, industrial and investigative applications, among others. In this paper, it is proposed to implement a three-dimensional (3D) reconstruction system for applications in superficial inspection of non-metallic pipes for the hydrocarbons transport. The system is formed by a CCD camera, a video-projector and a laptop and it is based on fringe projection technique. System functionality is evidenced by evaluating the quality of three-dimensional reconstructions obtained, which allow observing the failures and defects on the study object surface.

Turbomachinery design and tonal acoustics computations

NASA Technical Reports Server (NTRS)

Rangwalla, Akil A.

1995-01-01

The objective of this research was two-fold. The first objective was to complete the three-dimensional unsteady calculations of the flow through a new transonic turbine and study the effects of secondary flows due to the hub and casing, tip clearance vortices, and the inherent three-dimensional mixing of the flow. It should be noted that this turbine was and is still in the design phase and the results of the calculations have formed an integral part of the design process. The second objective of this proposal was to evaluate the capability of rotor-stator interaction codes to calculate tonal acoustics.

Calculus of nonrigid surfaces for geometry and texture manipulation.

PubMed

Bronstein, Alexander; Bronstein, Michael; Kimmel, Ron

2007-01-01

We present a geometric framework for automatically finding intrinsic correspondence between three-dimensional nonrigid objects. We model object deformation as near isometries and find the correspondence as the minimum-distortion mapping. A generalization of multidimensional scaling is used as the numerical core of our approach. As a result, we obtain the possibility to manipulate the extrinsic geometry and the texture of the objects as vectors in a linear space. We demonstrate our method on the problems of expression-invariant texture mapping onto an animated three-dimensional face, expression exaggeration, morphing between faces, and virtual body painting.

Synthesis and identification of three-dimensional faces from image(s) and three-dimensional generic models

NASA Astrophysics Data System (ADS)

Liu, Zexi; Cohen, Fernand

2017-11-01

We describe an approach for synthesizing a three-dimensional (3-D) face structure from an image or images of a human face taken at a priori unknown poses using gender and ethnicity specific 3-D generic models. The synthesis process starts with a generic model, which is personalized as images of the person become available using preselected landmark points that are tessellated to form a high-resolution triangular mesh. From a single image, two of the three coordinates of the model are reconstructed in accordance with the given image of the person, while the third coordinate is sampled from the generic model, and the appearance is made in accordance with the image. With multiple images, all coordinates and appearance are reconstructed in accordance with the observed images. This method allows for accurate pose estimation as well as face identification in 3-D rendering of a difficult two-dimensional (2-D) face recognition problem into a much simpler 3-D surface matching problem. The estimation of the unknown pose is achieved using the Levenberg-Marquardt optimization process. Encouraging experimental results are obtained in a controlled environment with high-resolution images under a good illumination condition, as well as for images taken in an uncontrolled environment under arbitrary illumination with low-resolution cameras.

Measuring sensitivity to viewpoint change with and without stereoscopic cues.

PubMed

Bell, Jason; Dickinson, Edwin; Badcock, David R; Kingdom, Frederick A A

2013-12-04

The speed and accuracy of object recognition is compromised by a change in viewpoint; demonstrating that human observers are sensitive to this transformation. Here we discuss a novel method for simulating the appearance of an object that has undergone a rotation-in-depth, and include an exposition of the differences between perspective and orthographic projections. Next we describe a method by which human sensitivity to rotation-in-depth can be measured. Finally we discuss an apparatus for creating a vivid percept of a 3-dimensional rotation-in-depth; the Wheatstone Eight Mirror Stereoscope. By doing so, we reveal a means by which to evaluate the role of stereoscopic cues in the discrimination of viewpoint rotated shapes and objects.

Multifunctional, three-dimensional tomography for analysis of eletrectrohydrodynamic jetting

NASA Astrophysics Data System (ADS)

Nguyen, Xuan Hung; Gim, Yeonghyeon; Ko, Han Seo

2015-05-01

A three-dimensional optical tomography technique was developed to reconstruct three-dimensional objects using a set of two-dimensional shadowgraphic images and normal gray images. From three high-speed cameras, which were positioned at an offset angle of 45° between each other, number, size, and location of electrohydrodynamic jets with respect to the nozzle position were analyzed using shadowgraphic tomography employing multiplicative algebraic reconstruction technique (MART). Additionally, a flow field inside a cone-shaped liquid (Taylor cone) induced under an electric field was observed using a simultaneous multiplicative algebraic reconstruction technique (SMART), a tomographic method for reconstructing light intensities of particles, combined with three-dimensional cross-correlation. Various velocity fields of circulating flows inside the cone-shaped liquid caused by various physico-chemical properties of liquid were also investigated.

Synchromodal optical in vivo imaging employing microlens array optics: a complete framework

NASA Astrophysics Data System (ADS)

Peter, Joerg

2013-03-01

A complete mathematical framework for preclinical optical imaging (OI) support comprising bioluminescence imaging (BLI), fluorescence surface imaging (FSI) and fluorescence optical tomography (FOT) is presented in which optical data is acquired by means of a microlens array (MLA) based light detector (MLA-D). The MLA-D has been developed to enable unique OI, especially in synchromodal operation with secondary imaging modalities (SIM) such as positron emission tomography (PET) or magnetic resonance imaging (MRI). An MLA-D consists of a (large-area) photon sensor array, a matched MLA for field-of-view definition, and a septum mask of specific geometry made of anodized aluminum that is positioned between the sensor and the MLA to suppresses light cross-talk and to shield the sensor's radiofrequency interference signal (essential when used inside an MRI system). The software framework, while freely parameterizable for any MLA-D, is tailored towards an OI prototype system for preclinical SIM application comprising a multitude of cylindrically assembled, gantry-mounted, simultaneously operating MLA-D's. Besides the MLA-D specificity, the framework incorporates excitation and illumination light-source declarations of large-field and point geometry to facilitate multispectral FSI and FOT as well as three-dimensional object recognition. When used in synchromodal operation, reconstructed tomographic SIM volume data can be used for co-modal image fusion and also as a prior for estimating the imaged object's 3D surface by means of gradient vector flow. Superimposed planar (without object prior) or surface-aligned inverse mapping can be performed to estimate and to fuse the emission light map with the boundary of the imaged object. Triangulation and subsequent optical reconstruction (FOT) or constrained flow estimation (BLI), both including the possibility of SIM priors, can be performed to estimate the internal three-dimensional emission light distribution. The framework is susceptible to a number of variables controlling convergence and computational speed. Utilization and performance is illustrated on experimentally acquired data employing the OI prototype system in stand-alone operation, and when integrated into an unmodified preclinical PET system performing synchromodal BLI-PET in vivo imaging.

Mom's shadow: structure-from-motion in newly hatched chicks as revealed by an imprinting procedure.

PubMed

Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio

2009-03-01

The ability to recognize three-dimensional objects from two-dimensional (2-D) displays was investigated in domestic chicks, focusing on the role of the object's motion. In Experiment 1 newly hatched chicks, imprinted on a three-dimensional (3-D) object, were allowed to choose between the shadows of the familiar object and of an object never seen before. In Experiments 2 and 3 random-dot displays were used to produce the perception of a solid shape only when set in motion. Overall, the results showed that domestic chicks were able to recognize familiar shapes from 2-D motion stimuli. It is likely that similar general mechanisms underlying the perception of structure-from-motion and the extraction of 3-D information are shared by humans and animals. The present data shows that they occur similarly in birds as known for mammals, two separate vertebrate classes; this possibly indicates a common phylogenetic origin of these processes.

Plot Scale Factor Models for Standard Orthographic Views

ERIC Educational Resources Information Center

Osakue, Edward E.

2007-01-01

Geometric modeling provides graphic representations of real or abstract objects. Realistic representation requires three dimensional (3D) attributes since natural objects have three principal dimensions. CAD software gives the user the ability to construct realistic 3D models of objects, but often prints of these models must be generated on two…

Further insight into self-face recognition in schizophrenia patients: Why ambiguity matters.

PubMed

Bortolon, Catherine; Capdevielle, Delphine; Salesse, Robin N; Raffard, Stephane

2016-03-01

Although some studies reported specifically self-face processing deficits in patients with schizophrenia disorder (SZ), it remains unclear whether these deficits rather reflect a more global face processing deficit. Contradictory results are probably due to the different methodologies employed and the lack of control of other confounding factors. Moreover, no study has so far evaluated possible daily life self-face recognition difficulties in SZ. Therefore, our primary objective was to investigate self-face recognition in patients suffering from SZ compared to healthy controls (HC) using an "objective measure" (reaction time and accuracy) and a "subjective measure" (self-report of daily self-face recognition difficulties). Twenty-four patients with SZ and 23 HC performed a self-face recognition task and completed a questionnaire evaluating daily difficulties in self-face recognition. Recognition task material consisted in three different faces (the own, a famous and an unknown) being morphed in steps of 20%. Results showed that SZ were overall slower than HC regardless of the face identity, but less accurate only for the faces containing 60%-40% morphing. Moreover, SZ and HC reported a similar amount of daily problems with self/other face recognition. No significant correlations were found between objective and subjective measures (p > 0.05). The small sample size and relatively mild severity of psychopathology does not allow us to generalize our results. These results suggest that: (1) patients with SZ are as capable of recognizing their own face as HC, although they are susceptible to ambiguity; (2) there are far less self recognition deficits in schizophrenia patients than previously postulated. Copyright © 2015 Elsevier Ltd. All rights reserved.

Flat holographic stereograms synthesized from computer-generated images by using LiNbO3 crystal

NASA Astrophysics Data System (ADS)

Qu, Zhi-Min; Liu, Jinsheng; Xu, Liangying

1991-02-01

In this paper we used a novel method for synthesizing computer gene rated images in which by means of a series of intermediate holograms recorded on Fe--doped LiNbO crystals a high quality flat stereograni with wide view angle and much deep 3D image ha been obtained. 2. INTRODUCTITJN As we all know the conventional holography is very limited. With the help of a contineous wave laser only stationary objects can be re corded due tO its insufficient power. Although some moving objects could be recorded by a pulsed laser the dimensions and kinds of object are restricted. If we would like to see a imaginary object or a three dimensional image designed by computer it is very difficult by means of above conventional holography. Of course if we have a two-dimensional image on a comouter screen we can rotate it to give a three-dimensional perspective but we can never really see it as a solid. However flat holographic stereograrns synthesized from computer generated images will make one directly see the comoute results in the form of 3D image. Obviously it will have wide applications in design architecture medicine education and arts. 406 / SPIE Vol. 1238 Three-Dimensional Holography: Science Culture Education (1989)

Face recognition based on two-dimensional discriminant sparse preserving projection

NASA Astrophysics Data System (ADS)

Zhang, Dawei; Zhu, Shanan

2018-04-01

In this paper, a supervised dimensionality reduction algorithm named two-dimensional discriminant sparse preserving projection (2DDSPP) is proposed for face recognition. In order to accurately model manifold structure of data, 2DDSPP constructs within-class affinity graph and between-class affinity graph by the constrained least squares (LS) and l1 norm minimization problem, respectively. Based on directly operating on image matrix, 2DDSPP integrates graph embedding (GE) with Fisher criterion. The obtained projection subspace preserves within-class neighborhood geometry structure of samples, while keeping away samples from different classes. The experimental results on the PIE and AR face databases show that 2DDSPP can achieve better recognition performance.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Forensic Facial Reconstruction: The Final Frontier.

PubMed

Gupta, Sonia; Gupta, Vineeta; Vij, Hitesh; Vij, Ruchieka; Tyagi, Nutan

2015-09-01

Forensic facial reconstruction can be used to identify unknown human remains when other techniques fail. Through this article, we attempt to review the different methods of facial reconstruction reported in literature. There are several techniques of doing facial reconstruction, which vary from two dimensional drawings to three dimensional clay models. With the advancement in 3D technology, a rapid, efficient and cost effective computerized 3D forensic facial reconstruction method has been developed which has brought down the degree of error previously encountered. There are several methods of manual facial reconstruction but the combination Manchester method has been reported to be the best and most accurate method for the positive recognition of an individual. Recognition allows the involved government agencies to make a list of suspected victims'. This list can then be narrowed down and a positive identification may be given by the more conventional method of forensic medicine. Facial reconstruction allows visual identification by the individual's family and associates to become easy and more definite.

Modeling Cometary Coma with a Three Dimensional, Anisotropic Multiple Scattering Distributed Processing Code

NASA Technical Reports Server (NTRS)

Luchini, Chris B.

1997-01-01

Development of camera and instrument simulations for space exploration requires the development of scientifically accurate models of the objects to be studied. Several planned cometary missions have prompted the development of a three dimensional, multi-spectral, anisotropic multiple scattering model of cometary coma.

Dual-dimensional microscopy: real-time in vivo three-dimensional observation method using high-resolution light-field microscopy and light-field display.

PubMed

Kim, Jonghyun; Moon, Seokil; Jeong, Youngmo; Jang, Changwon; Kim, Youngmin; Lee, Byoungho

2018-06-01

Here, we present dual-dimensional microscopy that captures both two-dimensional (2-D) and light-field images of an in-vivo sample simultaneously, synthesizes an upsampled light-field image in real time, and visualizes it with a computational light-field display system in real time. Compared with conventional light-field microscopy, the additional 2-D image greatly enhances the lateral resolution at the native object plane up to the diffraction limit and compensates for the image degradation at the native object plane. The whole process from capturing to displaying is done in real time with the parallel computation algorithm, which enables the observation of the sample's three-dimensional (3-D) movement and direct interaction with the in-vivo sample. We demonstrate a real-time 3-D interactive experiment with Caenorhabditis elegans. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Connectionist model-based stereo vision for telerobotics

NASA Technical Reports Server (NTRS)

Hoff, William; Mathis, Donald

1989-01-01

Autonomous stereo vision for range measurement could greatly enhance the performance of telerobotic systems. Stereo vision could be a key component for autonomous object recognition and localization, thus enabling the system to perform low-level tasks, and allowing a human operator to perform a supervisory role. The central difficulty in stereo vision is the ambiguity in matching corresponding points in the left and right images. However, if one has a priori knowledge of the characteristics of the objects in the scene, as is often the case in telerobotics, a model-based approach can be taken. Researchers describe how matching ambiguities can be resolved by ensuring that the resulting three-dimensional points are consistent with surface models of the expected objects. A four-layer neural network hierarchy is used in which surface models of increasing complexity are represented in successive layers. These models are represented using a connectionist scheme called parameter networks, in which a parametrized object (for example, a planar patch p=f(h,m sub x, m sub y) is represented by a collection of processing units, each of which corresponds to a distinct combination of parameter values. The activity level of each unit in the parameter network can be thought of as representing the confidence with which the hypothesis represented by that unit is believed. Weights in the network are set so as to implement gradient descent in an energy function.

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

PubMed

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

2010-02-11

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

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

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

PubMed

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

2014-07-03

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

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

PubMed

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

Three-dimensional shape analysis of miarolitic cavities and enclaves in the Kakkonda granite by X-ray computed tomography

NASA Astrophysics Data System (ADS)

Ohtani, Tomoyuki; Nakano, Tsukasa; Nakashima, Yoshito; Muraoka, Hirofumi

2001-11-01

Three-dimensional shape analysis of miarolitic cavities and enclaves from the Kakkonda granite, NE Japan, was performed by X-ray computed tomography (CT) and image analysis. The three-dimensional shape of the miarolitic cavities and enclaves was reconstructed by stacked two-dimensional CT slice images with an in-plane resolution of 0.3 mm and an inter-slice spacing of 1 mm. An ellipsoid was fitted to each reconstructed object by the image processing programs. The shortest, intermediate, and longest axes of the ellipsoids fitted to miarolitic cavities had E-W, N-S, and vertical directions, respectively. The shortest axes of the ellipsoids fitted to enclaves were sub-vertical to vertical. Three-dimensional strains calculated from miarolitic cavities and enclaves have E-W and vertical shortening, respectively. The shape characteristics of miarolitic cavities probably reflect regional stress during the late magmatic stage, and those of enclaves reflect shortening by later-intruded magma or body rotation during the early magmatic stage. The miarolitic cavities may not be strained homogeneously with the surrounding granite, because the competence of minerals is different from that of the fluid-filled cavities. Although the strain markers require sufficient contrast between their CT numbers and those of the surrounding minerals, this method has several advantages over conventional methods, including the fact that it is non-destructive, expedient, and allows direct three-dimensional observation of each object.

Space trajectory calculation based on G-sensor

NASA Astrophysics Data System (ADS)

Xu, Biya; Zhan, Yinwei; Shao, Yang

2017-08-01

At present, without full use of the mobile phone around us, most of the research in human body posture recognition field is use camera or portable acceleration sensor to collect data. In this paper, G-sensor built-in mobile phone is use to collect data. After processing data with the way of moving average filter and acceleration integral, joint point's space three-dimensional coordinates can be abtained accurately.

Supramolecular Lego assembly towards three-dimensional multi-responsive hydrogels.

PubMed

Ma, Chunxin; Li, Tiefeng; Zhao, Qian; Yang, Xuxu; Wu, Jingjun; Luo, Yingwu; Xie, Tao

2014-08-27

Inspired by the assembly of Lego toys, hydrogel building blocks with heterogeneous responsiveness are assembled utilizing macroscopic supramolecular recognition as the adhesion force. The Lego hydrogel provides 3D transformation upon pH variation. After disassembly of the building blocks by changing the oxidation state, they can be re-assembled into a completely new shape. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Leukocyte Recognition Using EM-Algorithm

NASA Astrophysics Data System (ADS)

Colunga, Mario Chirinos; Siordia, Oscar Sánchez; Maybank, Stephen J.

This document describes a method for classifying images of blood cells. Three different classes of cells are used: Band Neutrophils, Eosinophils and Lymphocytes. The image pattern is projected down to a lower dimensional sub space using PCA; the probability density function for each class is modeled with a Gaussian mixture using the EM-Algorithm. A new cell image is classified using the maximum a posteriori decision rule.

Prevalence of face recognition deficits in middle childhood.

PubMed

Bennetts, Rachel J; Murray, Ebony; Boyce, Tian; Bate, Sarah

2017-02-01

Approximately 2-2.5% of the adult population is believed to show severe difficulties with face recognition, in the absence of any neurological injury-a condition known as developmental prosopagnosia (DP). However, to date no research has attempted to estimate the prevalence of face recognition deficits in children, possibly because there are very few child-friendly, well-validated tests of face recognition. In the current study, we examined face and object recognition in a group of primary school children (aged 5-11 years), to establish whether our tests were suitable for children and to provide an estimate of face recognition difficulties in children. In Experiment 1 (n = 184), children completed a pre-existing test of child face memory, the Cambridge Face Memory Test-Kids (CFMT-K), and a bicycle test with the same format. In Experiment 2 (n = 413), children completed three-alternative forced-choice matching tasks with faces and bicycles. All tests showed good psychometric properties. The face and bicycle tests were well matched for difficulty and showed a similar developmental trajectory. Neither the memory nor the matching tests were suitable to detect impairments in the youngest groups of children, but both tests appear suitable to screen for face recognition problems in middle childhood. In the current sample, 1.2-5.2% of children showed difficulties with face recognition; 1.2-4% showed face-specific difficulties-that is, poor face recognition with typical object recognition abilities. This is somewhat higher than previous adult estimates: It is possible that face matching tests overestimate the prevalence of face recognition difficulties in children; alternatively, some children may "outgrow" face recognition difficulties.

Bistatic scattering from a three-dimensional object above a two-dimensional randomly rough surface modeled with the parallel FDTD approach.

PubMed

Guo, L-X; Li, J; Zeng, H

2009-11-01

We present an investigation of the electromagnetic scattering from a three-dimensional (3-D) object above a two-dimensional (2-D) randomly rough surface. A Message Passing Interface-based parallel finite-difference time-domain (FDTD) approach is used, and the uniaxial perfectly matched layer (UPML) medium is adopted for truncation of the FDTD lattices, in which the finite-difference equations can be used for the total computation domain by properly choosing the uniaxial parameters. This makes the parallel FDTD algorithm easier to implement. The parallel performance with different number of processors is illustrated for one rough surface realization and shows that the computation time of our parallel FDTD algorithm is dramatically reduced relative to a single-processor implementation. Finally, the composite scattering coefficients versus scattered and azimuthal angle are presented and analyzed for different conditions, including the surface roughness, the dielectric constants, the polarization, and the size of the 3-D object.

[Visual Texture Agnosia in Humans].

PubMed

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

Generalization between canonical and non-canonical views in object recognition

PubMed Central

Ghose, Tandra; Liu, Zili

2013-01-01

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

The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

Ubiquitous Geometry: Some Examples Showing the Significance of Size and Shape in the Works of Man and Nature.

ERIC Educational Resources Information Center

Bachman, C. H.

1988-01-01

Presents examples to show the ubiquitous nature of geometry. Illustrates the relationship between the perimeter and area of two-dimensional objects and between the area and volume of three-dimensional objects. Provides examples of distribution systems, optimum shapes, structural strength, biological heat engines, man's size, and reflection and…

Handheld laser scanner automatic registration based on random coding

NASA Astrophysics Data System (ADS)

He, Lei; Yu, Chun-ping; Wang, Li

2011-06-01

Current research on Laser Scanner often focuses mainly on the static measurement. Little use has been made of dynamic measurement, that are appropriate for more problems and situations. In particular, traditional Laser Scanner must Keep stable to scan and measure coordinate transformation parameters between different station. In order to make the scanning measurement intelligently and rapidly, in this paper ,we developed a new registration algorithm for handleheld laser scanner based on the positon of target, which realize the dynamic measurement of handheld laser scanner without any more complex work. the double camera on laser scanner can take photograph of the artificial target points to get the three-dimensional coordinates, this points is designed by random coding. And then, a set of matched points is found from control points to realize the orientation of scanner by the least-square common points transformation. After that the double camera can directly measure the laser point cloud in the surface of object and get the point cloud data in an unified coordinate system. There are three major contributions in the paper. Firstly, a laser scanner based on binocular vision is designed with double camera and one laser head. By those, the real-time orientation of laser scanner is realized and the efficiency is improved. Secondly, the coding marker is introduced to solve the data matching, a random coding method is proposed. Compared with other coding methods,the marker with this method is simple to match and can avoid the shading for the object. Finally, a recognition method of coding maker is proposed, with the use of the distance recognition, it is more efficient. The method present here can be used widely in any measurement from small to huge obiect, such as vehicle, airplane which strengthen its intelligence and efficiency. The results of experiments and theory analzing demonstrate that proposed method could realize the dynamic measurement of handheld laser scanner. Theory analysis and experiment shows the method is reasonable and efficient.

Recognition of Equations Using a Two-Dimensional Stochastic Context-Free Grammar

NASA Astrophysics Data System (ADS)

Chou, Philip A.

1989-11-01

We propose using two-dimensional stochastic context-free grammars for image recognition, in a manner analogous to using hidden Markov models for speech recognition. The value of the approach is demonstrated in a system that recognizes printed, noisy equations. The system uses a two-dimensional probabilistic version of the Cocke-Younger-Kasami parsing algorithm to find the most likely parse of the observed image, and then traverses the corresponding parse tree in accordance with translation formats associated with each production rule, to produce eqn I troff commands for the imaged equation. In addition, it uses two-dimensional versions of the Inside/Outside and Baum re-estimation algorithms for learning the parameters of the grammar from a training set of examples. Parsing the image of a simple noisy equation currently takes about one second of cpu time on an Alliant FX/80.

Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

2001-03-01

This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

Forced free-shear layer measurements

NASA Technical Reports Server (NTRS)

Leboeuf, Richard L.

1994-01-01

Detailed three-dimensional three-component phase averaged measurements of the spanwise and streamwise vorticity formation and evolution in acoustically forced plane free-shear flows have been obtained. For the first time, phase-averaged measurements of all three velocity components have been obtained in both a mixing layer and a wake on three-dimensional grids, yielding the spanwise and streamwise vorticity distributions without invoking Taylor's hypothesis. Initially, two-frequency forcing was used to phase-lock the roll-up and first pairing of the spanwise vortical structures in a plane mixing layer. The objective of this study was to measure the near-field vortical structure morphology in a mixing layer with 'natural' laminar initial boundary layers. For the second experiment the second and third subharmonics of the fundamental roll-up frequency were added to the previous two-frequency forcing in order to phase-lock the roll-up and first three pairings of the spanwise rollers in the mixing layer. The objective of this study was to determine the details of spanwise scale changes observed in previous time-averaged measurements and flow visualization of unforced mixing layers. For the final experiment, single-frequency forcing was used to phase-lock the Karman vortex street in a plane wake developing from nominally two-dimensional laminar initial boundary layers. The objective of this study was to compare measurements of the three-dimensional structure in a wake developing from 'natural' initial boundary layers to existing models of wake vortical structure.

Evaluation of a 3D stereophotogrammetric technique to measure the stone casts of patients with unilateral cleft lip and palate.

PubMed

Sforza, Chiarella; De Menezes, Marcio; Bresciani, Elena; Cerón-Zapata, Ana M; López-Palacio, Ana M; Rodriguez-Ardila, Myriam J; Berrio-Gutiérrez, Lina M

2012-07-01

To assess a three-dimensional stereophotogrammetric method for palatal cast digitization of children with unilateral cleft lip and palate. As part of a collaboration between the University of Milan (Italy) and the University CES of Medellin (Colombia), 96 palatal cast models obtained from neonatal patients with unilateral cleft lip and palate were obtained and digitized using a three-dimensional stereophotogrammetric imaging system. Three-dimensional measurements (cleft width, depth, length) were made separately for the longer and shorter cleft segments on the digital dental cast surface between landmarks, previously marked. Seven linear measurements were computed. Systematic and random errors between operators' tracings, and accuracy on geometric objects of known size were calculated. In addition, mean measurements from three-dimensional stereophotographs were compared statistically with those from direct anthropometry. The three-dimensional method presented good accuracy error (<0.9%) on measuring geometric objects. No systematic errors between operators' measurements were found (p > .05). Statistically significant differences (p < 5%) were noted for different methods (caliper versus stereophotogrammetry) for almost all distances analyzed, with mean absolute difference values ranging between 0.22 and 3.41 mm. Therefore, rates for the technical error of measurement and relative error magnitude were scored as moderate for Ag-Am and poor for Ag-Pg and Am-Pm distances. Generally, caliper values were larger than three-dimensional stereophotogrammetric values. Three-dimensional stereophotogrammetric systems have some advantages over direct anthropometry, and therefore the method could be sufficiently precise and accurate on palatal cast digitization with unilateral cleft lip and palate. This would be useful for clinical analyses in maxillofacial, plastic, and aesthetic surgery.

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

PubMed

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

2017-07-01

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

Plant recognition of Bradyrhizobium japonicum nod factors. Final report, September 15, 1992--March 14, 1997

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

Stacey, G.

1998-01-01

This grant had three objectives: (1) isolate and identify the unique nod factor metabolites made by different wild-type B. japonicum strains; (2) investigate the biological activity of these unique nod factors, especially as it relates to host range; and (3) initiate studies to define the mechanism of plant recognition of the nod factors. This report summarizes the results of this research.

Rapid response learning of brand logo priming: Evidence that brand priming is not dominated by rapid response learning.

PubMed

Boehm, Stephan G; Smith, Ciaran; Muench, Niklas; Noble, Kirsty; Atherton, Catherine

2017-08-31

Repetition priming increases the accuracy and speed of responses to repeatedly processed stimuli. Repetition priming can result from two complementary sources: rapid response learning and facilitation within perceptual and conceptual networks. In conceptual classification tasks, rapid response learning dominates priming of object recognition, but it does not dominate priming of person recognition. This suggests that the relative engagement of network facilitation and rapid response learning depends on the stimulus domain. Here, we addressed the importance of the stimulus domain for rapid response learning by investigating priming in another domain, brands. In three experiments, participants performed conceptual decisions for brand logos. Strong priming was present, but it was not dominated by rapid response learning. These findings add further support to the importance of the stimulus domain for the relative importance of network facilitation and rapid response learning, and they indicate that brand priming is more similar to person recognition priming than object recognition priming, perhaps because priming of both brands and persons requires individuation.

Eye movements during object recognition in visual agnosia.

PubMed

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

2012-07-01

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

The interplay of holistic shape, local feature and color information in object categorization.

PubMed

Rokszin, Adrienn Aranka; Győri-Dani, Dóra; Linnert, Szilvia; Krajcsi, Attila; Tompa, Tamás; Csifcsák, Gábor

2015-07-01

Although it is widely accepted that colors facilitate object and scene recognition under various circumstances, several studies found no effects of color removal in tasks requiring categorization of briefly presented animals in natural scenes. In this study, three experiments were performed to test the assumption that the discrepancy between empirical data is related to variations of the available meaningful global information such as object shapes and contextual cues. Sixty-one individuals categorized chromatic and achromatic versions of intact and scrambled images containing either cars or birds. While color removal did not affect the classification of intact stimuli, the recognition of moderately scrambled achromatic images was more difficult. This effect was accompanied by amplitude modulations of occipital event-related potentials emerging from approximately 150ms post-stimulus. Our results indicate that colors facilitate stimulus classification, but this effect becomes prominent only in cases when holistic processing is not sufficient for stimulus recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2011-09-01

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

The role of perceptual load in object recognition.

PubMed

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

2009-10-01

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

Body-wide anatomy recognition in PET/CT images

NASA Astrophysics Data System (ADS)

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

2015-03-01

With the rapid growth of positron emission tomography/computed tomography (PET/CT)-based medical applications, body-wide anatomy recognition on whole-body PET/CT images becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem and seldom studied due to unclear anatomy reference frame and low spatial resolution of PET images as well as low contrast and spatial resolution of the associated low-dose CT images. We previously developed an automatic anatomy recognition (AAR) system [15] whose applicability was demonstrated on diagnostic computed tomography (CT) and magnetic resonance (MR) images in different body regions on 35 objects. The aim of the present work is to investigate strategies for adapting the previous AAR system to low-dose CT and PET images toward automated body-wide disease quantification. Our adaptation of the previous AAR methodology to PET/CT images in this paper focuses on 16 objects in three body regions - thorax, abdomen, and pelvis - and consists of the following steps: collecting whole-body PET/CT images from existing patient image databases, delineating all objects in these images, modifying the previous hierarchical models built from diagnostic CT images to account for differences in appearance in low-dose CT and PET images, automatically locating objects in these images following object hierarchy, and evaluating performance. Our preliminary evaluations indicate that the performance of the AAR approach on low-dose CT images achieves object localization accuracy within about 2 voxels, which is comparable to the accuracies achieved on diagnostic contrast-enhanced CT images. Object recognition on low-dose CT images from PET/CT examinations without requiring diagnostic contrast-enhanced CT seems feasible.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Color Constancy in Two-Dimensional and Three-Dimensional Scenes: Effects of Viewing Methods and Surface Texture.

PubMed

Morimoto, Takuma; Mizokami, Yoko; Yaguchi, Hirohisa; Buck, Steven L

2017-01-01

There has been debate about how and why color constancy may be better in three-dimensional (3-D) scenes than in two-dimensional (2-D) scenes. Although some studies have shown better color constancy for 3-D conditions, the role of specific cues remains unclear. In this study, we compared color constancy for a 3-D miniature room (a real scene consisting of actual objects) and 2-D still images of that room presented on a monitor using three viewing methods: binocular viewing, monocular viewing, and head movement. We found that color constancy was better for the 3-D room; however, color constancy for the 2-D image improved when the viewing method caused the scene to be perceived more like a 3-D scene. Separate measurements of the perceptual 3-D effect of each viewing method also supported these results. An additional experiment comparing a miniature room and its image with and without texture suggested that surface texture of scene objects contributes to color constancy.

Investigating the Role of Surface Materials and Three Dimensional Architecture on In Vitro Differentiation of Porcine Monocyte-Derived Dendritic Cells

PubMed Central

Hartmann, Sofie Bruun; Mohanty, Soumyaranjan; Skovgaard, Kerstin; Brogaard, Louise; Flagstad, Frederikke Bjergvang; Emnéus, Jenny; Wolff, Anders; Summerfield, Artur; Jungersen, Gregers

2016-01-01

In vitro generation of dendritic-like cells through differentiation of peripheral blood monocytes is typically done using two-dimensional polystyrene culture plates. In the process of optimising cell culture techniques, engineers have developed fluidic micro-devises usually manufactured in materials other than polystyrene and applying three-dimensional structures more similar to the in vivo environment. Polydimethylsiloxane (PDMS) is an often used polymer for lab-on-a-chip devices but not much is known about the effect of changing the culture surface material from polystyrene to PDMS. In the present study the differentiation of porcine monocytes to monocyte-derived dendritic cells (moDCs) was investigated using CD172apos pig blood monocytes stimulated with GM-CSF and IL-4. Monocytes were cultured on surfaces made of two- and three-dimensional polystyrene as well as two- and three-dimensional PDMS and carbonised three-dimensional PDMS. Cells cultured conventionally (on two-dimensional polystyrene) differentiated into moDCs as expected. Interestingly, gene expression of a wide range of cytokines, chemokines, and pattern recognition receptors was influenced by culture surface material and architecture. Distinct clustering of cells, based on similar expression patterns of 46 genes of interest, was seen for cells isolated from two- and three-dimensional polystyrene as well as two- and three-dimensional PDMS. Changing the material from polystyrene to PDMS resulted in cells with expression patterns usually associated with macrophage expression (upregulation of CD163 and downregulation of CD1a, FLT3, LAMP3 and BATF3). However, this was purely based on gene expression level, and no functional assays were included in this study which would be necessary in order to classify the cells as being macrophages. When changing to three-dimensional culture the cells became increasingly activated in terms of IL6, IL8, IL10 and CCR5 gene expression. Further stimulation with LPS resulted in a slight increase in the expression of maturation markers (SLA-DRB1, CD86 and CD40) as well as cytokines (IL6, IL8, IL10 and IL23A) but the influence of the surfaces was unchanged. These findings highlights future challenges of combining and comparing data generated from microfluidic cell culture-devices made using alternative materials to data generated using conventional polystyrene plates used by most laboratories today. PMID:27362493

Investigating the Role of Surface Materials and Three Dimensional Architecture on In Vitro Differentiation of Porcine Monocyte-Derived Dendritic Cells.

PubMed

Hartmann, Sofie Bruun; Mohanty, Soumyaranjan; Skovgaard, Kerstin; Brogaard, Louise; Flagstad, Frederikke Bjergvang; Emnéus, Jenny; Wolff, Anders; Summerfield, Artur; Jungersen, Gregers

2016-01-01

In vitro generation of dendritic-like cells through differentiation of peripheral blood monocytes is typically done using two-dimensional polystyrene culture plates. In the process of optimising cell culture techniques, engineers have developed fluidic micro-devises usually manufactured in materials other than polystyrene and applying three-dimensional structures more similar to the in vivo environment. Polydimethylsiloxane (PDMS) is an often used polymer for lab-on-a-chip devices but not much is known about the effect of changing the culture surface material from polystyrene to PDMS. In the present study the differentiation of porcine monocytes to monocyte-derived dendritic cells (moDCs) was investigated using CD172apos pig blood monocytes stimulated with GM-CSF and IL-4. Monocytes were cultured on surfaces made of two- and three-dimensional polystyrene as well as two- and three-dimensional PDMS and carbonised three-dimensional PDMS. Cells cultured conventionally (on two-dimensional polystyrene) differentiated into moDCs as expected. Interestingly, gene expression of a wide range of cytokines, chemokines, and pattern recognition receptors was influenced by culture surface material and architecture. Distinct clustering of cells, based on similar expression patterns of 46 genes of interest, was seen for cells isolated from two- and three-dimensional polystyrene as well as two- and three-dimensional PDMS. Changing the material from polystyrene to PDMS resulted in cells with expression patterns usually associated with macrophage expression (upregulation of CD163 and downregulation of CD1a, FLT3, LAMP3 and BATF3). However, this was purely based on gene expression level, and no functional assays were included in this study which would be necessary in order to classify the cells as being macrophages. When changing to three-dimensional culture the cells became increasingly activated in terms of IL6, IL8, IL10 and CCR5 gene expression. Further stimulation with LPS resulted in a slight increase in the expression of maturation markers (SLA-DRB1, CD86 and CD40) as well as cytokines (IL6, IL8, IL10 and IL23A) but the influence of the surfaces was unchanged. These findings highlights future challenges of combining and comparing data generated from microfluidic cell culture-devices made using alternative materials to data generated using conventional polystyrene plates used by most laboratories today.

A Hidden Surface Algorithm for Computer Generated Halftone Pictures

DTIC Science & Technology

converting data describing three-dimensional objects into data that can be used to generate two-dimensional halftone images. It deals with some problems that arise in black and white, and color shading.

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

PubMed

Janko, Vito; Luštrek, Mitja

2017-12-29

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

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

PubMed Central

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

2011-01-01

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

Acoustic scattering by arbitrary distributions of disjoint, homogeneous cylinders or spheres.

PubMed

Hesford, Andrew J; Astheimer, Jeffrey P; Waag, Robert C

2010-05-01

A T-matrix formulation is presented to compute acoustic scattering from arbitrary, disjoint distributions of cylinders or spheres, each with arbitrary, uniform acoustic properties. The generalized approach exploits the similarities in these scattering problems to present a single system of equations that is easily specialized to cylindrical or spherical scatterers. By employing field expansions based on orthogonal harmonic functions, continuity of pressure and normal particle velocity are directly enforced at each scatterer using diagonal, analytic expressions to eliminate the need for integral equations. The effect of a cylinder or sphere that encloses all other scatterers is simulated with an outer iterative procedure that decouples the inner-object solution from the effect of the enclosing object to improve computational efficiency when interactions among the interior objects are significant. Numerical results establish the validity and efficiency of the outer iteration procedure for nested objects. Two- and three-dimensional methods that employ this outer iteration are used to measure and characterize the accuracy of two-dimensional approximations to three-dimensional scattering of elevation-focused beams.

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

PubMed

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

2002-01-01

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

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

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1994-01-01

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

Spider-web inspired multi-resolution graphene tactile sensor.

PubMed

Liu, Lu; Huang, Yu; Li, Fengyu; Ma, Ying; Li, Wenbo; Su, Meng; Qian, Xin; Ren, Wanjie; Tang, Kanglai; Song, Yanlin

2018-05-08

Multi-dimensional accurate response and smooth signal transmission are critical challenges in the advancement of multi-resolution recognition and complex environment analysis. Inspired by the structure-activity relationship between discrepant microstructures of the spiral and radial threads in a spider web, we designed and printed graphene with porous and densely-packed microstructures to integrate into a multi-resolution graphene tactile sensor. The three-dimensional (3D) porous graphene structure performs multi-dimensional deformation responses. The laminar densely-packed graphene structure contributes excellent conductivity with flexible stability. The spider-web inspired printed pattern inherits orientational and locational kinesis tracking. The multi-structure construction with homo-graphene material can integrate discrepant electronic properties with remarkable flexibility, which will attract enormous attention for electronic skin, wearable devices and human-machine interactions.

The structure of Escherichia coli signal recognition particle revealed by scanning transmission electron microscopy.

PubMed

Mainprize, Iain L; Beniac, Daniel R; Falkovskaia, Elena; Cleverley, Robert M; Gierasch, Lila M; Ottensmeyer, F Peter; Andrews, David W

2006-12-01

Structural studies on various domains of the ribonucleoprotein signal recognition particle (SRP) have not converged on a single complete structure of bacterial SRP consistent with the biochemistry of the particle. We obtained a three-dimensional structure for Escherichia coli SRP by cryoscanning transmission electron microscopy and mapped the internal RNA by electron spectroscopic imaging. Crystallographic data were fit into the SRP reconstruction, and although the resulting model differed from previous models, they could be rationalized by movement through an interdomain linker of Ffh, the protein component of SRP. Fluorescence resonance energy transfer experiments determined interdomain distances that were consistent with our model of SRP. Docking our model onto the bacterial ribosome suggests a mechanism for signal recognition involving interdomain movement of Ffh into and out of the nascent chain exit site and suggests how SRP could interact and/or compete with the ribosome-bound chaperone, trigger factor, for a nascent chain during translation.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

PubMed

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

Optimal wavelength band clustering for multispectral iris recognition.

PubMed

Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

FpvA-mediated ferric pyoverdine uptake in Pseudomonas aeruginosa: identification of aromatic residues in FpvA implicated in ferric pyoverdine binding and transport.

PubMed

Shen, Jiang-Sheng; Geoffroy, Valérie; Neshat, Shadi; Jia, Zongchao; Meldrum, Allison; Meyer, Jean-Marie; Poole, Keith

2005-12-01

A number of aromatic residues were seen to cluster in the upper portion of the three-dimensional structure of the FpvA ferric pyoverdine receptor of Pseudomonas aeruginosa, reminiscent of the aromatic binding pocket for ferrichrome in the FhuA receptor of Escherichia coli. Alanine substitutions in three of these, W362, W391, and F795, markedly compromised ferric pyoverdine binding and transport, consistent with a role of FpvA in ferric pyoverdine recognition.

Methods for preparation of three-dimensional bodies

DOEpatents

Mulligan, Anthony C.; Rigali, Mark J.; Sutaria, Manish P.; Artz, Gregory J.; Gafner, Felix H.; Vaidyanathan, K. Ranji

2004-09-28

Processes for mechanically fabricating two and three-dimensional fibrous monolith composites include preparing a fibrous monolith filament from a core composition of a first powder material and a boundary material of a second powder material. The filament includes a first portion of the core composition surrounded by a second portion of the boundary composition. One or more filaments are extruded through a mechanically-controlled deposition nozzle onto a working surface to create a fibrous monolith composite object. The objects may be formed directly from computer models and have complex geometries.

Methods for preparation of three-dimensional bodies

DOEpatents

Mulligan, Anthony C [Tucson, AZ; Rigali, Mark J [Carlsbad, NM; Sutaria, Manish P [Malden, MA; Artz, Gregory J [Tucson, AZ; Gafner, Felix H [Tucson, AZ; Vaidyanathan, K Ranji [Tucson, AZ

2008-06-17

Processes for mechanically fabricating two and three-dimensional fibrous monolith composites include preparing a fibrous monolith filament from a core composition of a first powder material and a boundary material of a second powder material. The filament includes a first portion of the core composition surrounded by a second portion of the boundary composition. One or more filaments are extruded through a mechanically-controlled deposition nozzle onto a working surface to create a fibrous monolith composite object. The objects may be formed directly from computer models and have complex geometries.

Three-dimensional orientation-unlimited polarization encryption by a single optically configured vectorial beam.

PubMed

Li, Xiangping; Lan, Tzu-Hsiang; Tien, Chung-Hao; Gu, Min

2012-01-01

The interplay between light polarization and matter is the basis of many fundamental physical processes and applications. However, the electromagnetic wave nature of light in free space sets a fundamental limit on the three-dimensional polarization orientation of a light beam. Although a high numerical aperture objective can be used to bend the wavefront of a radially polarized beam to generate the longitudinal polarization state in the focal volume, the arbitrary three-dimensional polarization orientation of a beam has not been achieved yet. Here we present a novel technique for generating arbitrary three-dimensional polarization orientation by a single optically configured vectorial beam. As a consequence, by applying this technique to gold nanorods, orientation-unlimited polarization encryption with ultra-security is demonstrated. These results represent a new landmark of the orientation-unlimited three-dimensional polarization control of the light-matter interaction.

Human Consequences of Agile Aircraft (Facteurs humains lies au pilotage des avions de combat tres manoeuvrants)

DTIC Science & Technology

2001-05-01

displays were discussed with the test pilots that we interviewed. The pilots had mixed opinions on tactile and auditory displays. Positive comments...were noted concerning three-dimensional auditory displays, although some stated that the pilot could easily ignore the aural tone. Others complained...recognition technology was not reliable enough and worried about problems with surrounding auditory signals from anti-G straining maneuvers, oxygen

Physical signals for protein-DNA recognition

NASA Astrophysics Data System (ADS)

Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

2009-09-01

This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein-DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do.

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.

Building a Three-Dimensional Nano-Bio Interface for Aptasensing: An Analytical Methodology Based on Steric Hindrance Initiated Signal Amplification Effect.

PubMed

Du, Xiaojiao; Jiang, Ding; Hao, Nan; Qian, Jing; Dai, Liming; Zhou, Lei; Hu, Jianping; Wang, Kun

2016-10-04

The development of novel detection methodologies in electrochemiluminescence (ECL) aptasensor fields with simplicity and ultrasensitivity is essential for constructing biosensing architectures. Herein, a facile, specific, and sensitive methodology was developed unprecedentedly for quantitative detection of microcystin-LR (MC-LR) based on three-dimensional boron and nitrogen codoped graphene hydrogels (BN-GHs) assisted steric hindrance amplifying effect between the aptamer and target analytes. The recognition reaction was monitored by quartz crystal microbalance (QCM) to validate the possible steric hindrance effect. First, the BN-GHs were synthesized via self-assembled hydrothermal method and then applied as the Ru(bpy) 3 2+ immobilization platform for further loading the biomolecule aptamers due to their nanoporous structure and large specific surface area. Interestingly, we discovered for the first time that, without the aid of conventional double-stranded DNA configuration, such three-dimensional nanomaterials can directly amplify the steric hindrance effect between the aptamer and target analytes to a detectable level, and this facile methodology could be for an exquisite assay. With the MC-LR as a model, this novel ECL biosensor showed a high sensitivity and a wide linear range. This strategy supplies a simple and versatile platform for specific and sensitive determination of a wide range of aptamer-related targets, implying that three-dimensional nanomaterials would play a crucial role in engineering and developing novel detection methodologies for ECL aptasensing fields.

Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis

PubMed Central

Fang, Shiaofen; McLaughlin, Jason; Fang, Jiandong; Huang, Jeffrey; Autti-Rämö, Ilona; Fagerlund, Åse; Jacobson, Sandra W.; Robinson, Luther K.; Hoyme, H. Eugene; Mattson, Sarah N.; Riley, Edward; Zhou, Feng; Ward, Richard; Moore, Elizabeth S.; Foroud, Tatiana

2012-01-01

Objectives Use three-dimensional (3D) facial laser scanned images from children with fetal alcohol syndrome (FAS) and controls to develop an automated diagnosis technique that can reliably and accurately identify individuals prenatally exposed to alcohol. Methods A detailed dysmorphology evaluation, history of prenatal alcohol exposure, and 3D facial laser scans were obtained from 149 individuals (86 FAS; 63 Control) recruited from two study sites (Cape Town, South Africa and Helsinki, Finland). Computer graphics, machine learning, and pattern recognition techniques were used to automatically identify a set of facial features that best discriminated individuals with FAS from controls in each sample. Results An automated feature detection and analysis technique was developed and applied to the two study populations. A unique set of facial regions and features were identified for each population that accurately discriminated FAS and control faces without any human intervention. Conclusion Our results demonstrate that computer algorithms can be used to automatically detect facial features that can discriminate FAS and control faces. PMID:18713153

Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit.

PubMed

Yi, Faliu; Lee, Jieun; Moon, Inkyu

2014-05-01

The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.

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.

A Quantitative Technique for Beginning Microscopists.

ERIC Educational Resources Information Center

Sundberg, Marshall D.

1984-01-01

Stereology is the study of three-dimensional objects through the interpretation of two-dimensional images. Stereological techniques used in introductory botany to quantitatively examine changes in leaf anatomy in response to different environments are discussed. (JN)

Jini service to reconstruct tomographic data

NASA Astrophysics Data System (ADS)

Knoll, Peter; Mirzaei, S.; Koriska, K.; Koehn, H.

2002-06-01

A number of imaging systems rely on the reconstruction of a 3- dimensional model from its projections through the process of computed tomography (CT). In medical imaging, for example magnetic resonance imaging (MRI), positron emission tomography (PET), and Single Computer Tomography (SPECT) acquire two-dimensional projections of a three dimensional projections of a three dimensional object. In order to calculate the 3-dimensional representation of the object, i.e. its voxel distribution, several reconstruction algorithms have been developed. Currently, mainly two reconstruct use: the filtered back projection(FBP) and iterative methods. Although the quality of iterative reconstructed SPECT slices is better than that of FBP slices, such iterative algorithms are rarely used for clinical routine studies because of their low availability and increased reconstruction time. We used Jini and a self-developed iterative reconstructions algorithm to design and implement a Jini reconstruction service. With this service, the physician selects the patient study from a database and a Jini client automatically discovers the registered Jini reconstruction services in the department's Intranet. After downloading the proxy object the this Jini service, the SPECT acquisition data are reconstructed. The resulting transaxial slices are visualized using a Jini slice viewer, which can be used for various imaging modalities.

Processing And Display Of Medical Three Dimensional Arrays Of Numerical Data Using Octree Encoding

NASA Astrophysics Data System (ADS)

Amans, Jean-Louis; Darier, Pierre

1986-05-01

imaging modalities such as X-Ray computerized Tomography (CT), Nuclear Medecine and Nuclear Magnetic Resonance can produce three-dimensional (3-D) arrays of numerical data of medical object internal structures. The analysis of 3-D data by synthetic generation of realistic images is an important area of computer graphics and imaging.

Three-Dimensional Interpretation of Sculptural Heritage with Digital and Tangible 3D Printed Replicas

ERIC Educational Resources Information Center

Saorin, José Luis; Carbonell-Carrera, Carlos; Cantero, Jorge de la Torre; Meier, Cecile; Aleman, Drago Diaz

2017-01-01

Spatial interpretation features as a skill to acquire in the educational curricula. The visualization and interpretation of three-dimensional objects in tactile devices and the possibility of digital manufacturing with 3D printers, offers an opportunity to include replicas of sculptures in teaching and, thus, facilitate the 3D interpretation of…

Using Virtual Worlds to Identify Multidimensional Student Engagement in High School Foreign Language Learning Classrooms

ERIC Educational Resources Information Center

Jacob, Laura Beth

2012-01-01

Virtual world environments have evolved from object-oriented, text-based online games to complex three-dimensional immersive social spaces where the lines between reality and computer-generated begin to blur. Educators use virtual worlds to create engaging three-dimensional learning spaces for students, but the impact of virtual worlds in…

SABRINA: an interactive solid geometry modeling program for Monte Carlo

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

West, J.T.

SABRINA is a fully interactive three-dimensional geometry modeling program for MCNP. In SABRINA, a user interactively constructs either body geometry, or surface geometry models, and interactively debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces the effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo Analysis.

A Comparison of Cognitive Teaching Stimuli in a First Grade Classroom.

ERIC Educational Resources Information Center

Sigrest, Christine E.

A study assessed the effectiveness of three cognitive levels of instruction with first graders--three-dimensional (3-D) instruction using real objects, two-dimensional (2-D) instruction using picture representations, and verbal instruction. The study population included 18 first-grade students between the ages of 6 and 8 at a small elementary city…

Augmented reality glass-free three-dimensional display with the stereo camera

NASA Astrophysics Data System (ADS)

Pang, Bo; Sang, Xinzhu; Chen, Duo; Xing, Shujun; Yu, Xunbo; Yan, Binbin; Wang, Kuiru; Yu, Chongxiu

2017-10-01

An improved method for Augmented Reality (AR) glass-free three-dimensional (3D) display based on stereo camera used for presenting parallax contents from different angle with lenticular lens array is proposed. Compared with the previous implementation method of AR techniques based on two-dimensional (2D) panel display with only one viewpoint, the proposed method can realize glass-free 3D display of virtual objects and real scene with 32 virtual viewpoints. Accordingly, viewers can get abundant 3D stereo information from different viewing angles based on binocular parallax. Experimental results show that this improved method based on stereo camera can realize AR glass-free 3D display, and both of virtual objects and real scene have realistic and obvious stereo performance.

Scene analysis for effective visual search in rough three-dimensional-modeling scenes

NASA Astrophysics Data System (ADS)

Wang, Qi; Hu, Xiaopeng

2016-11-01

Visual search is a fundamental technology in the computer vision community. It is difficult to find an object in complex scenes when there exist similar distracters in the background. We propose a target search method in rough three-dimensional-modeling scenes based on a vision salience theory and camera imaging model. We give the definition of salience of objects (or features) and explain the way that salience measurements of objects are calculated. Also, we present one type of search path that guides to the target through salience objects. Along the search path, when the previous objects are localized, the search region of each subsequent object decreases, which is calculated through imaging model and an optimization method. The experimental results indicate that the proposed method is capable of resolving the ambiguities resulting from distracters containing similar visual features with the target, leading to an improvement of search speed by over 50%.

Integrated Aeromechanics with Three-Dimensional Solid-Multibody Structures

NASA Technical Reports Server (NTRS)

Datta, Anubhav; Johnson, Wayne

2014-01-01

A full three-dimensional finite element-multibody structural dynamic solver is coupled to a three-dimensional Reynolds-averaged Navier-Stokes solver for the prediction of integrated aeromechanical stresses and strains on a rotor blade in forward flight. The objective is to lay the foundations of all major pieces of an integrated three-dimensional rotor dynamic analysis - from model construction to aeromechanical solution to stress/strain calculation. The primary focus is on the aeromechanical solution. Two types of three-dimensional CFD/CSD interfaces are constructed for this purpose with an emphasis on resolving errors from geometry mis-match so that initial-stage approximate structural geometries can also be effectively analyzed. A three-dimensional structural model is constructed as an approximation to a UH-60A-like fully articulated rotor. The aerodynamic model is identical to the UH-60A rotor. For preliminary validation measurements from a UH-60A high speed flight is used where CFD coupling is essential to capture the advancing side tip transonic effects. The key conclusion is that an integrated aeromechanical analysis is indeed possible with three-dimensional structural dynamics but requires a careful description of its geometry and discretization of its parts.

Phase in Optical Image Processing

NASA Astrophysics Data System (ADS)

Naughton, Thomas J.

2010-04-01

The use of phase has a long standing history in optical image processing, with early milestones being in the field of pattern recognition, such as VanderLugt's practical construction technique for matched filters, and (implicitly) Goodman's joint Fourier transform correlator. In recent years, the flexibility afforded by phase-only spatial light modulators and digital holography, for example, has enabled many processing techniques based on the explicit encoding and decoding of phase. One application area concerns efficient numerical computations. Pushing phase measurement to its physical limits, designs employing the physical properties of phase have ranged from the sensible to the wonderful, in some cases making computationally easy problems easier to solve and in other cases addressing mathematics' most challenging computationally hard problems. Another application area is optical image encryption, in which, typically, a phase mask modulates the fractional Fourier transformed coefficients of a perturbed input image, and the phase of the inverse transform is then sensed as the encrypted image. The inherent linearity that makes the system so elegant mitigates against its use as an effective encryption technique, but we show how a combination of optical and digital techniques can restore confidence in that security. We conclude with the concept of digital hologram image processing, and applications of same that are uniquely suited to optical implementation, where the processing, recognition, or encryption step operates on full field information, such as that emanating from a coherently illuminated real-world three-dimensional object.

Clinical utility of three-dimensional contrast-enhanced ultrasound in the differentiation between noninvasive and invasive neoplasms of urinary bladder.

PubMed

Li, Qiu-yang; Tang, Jie; He, En-hui; Li, Yan-mi; Zhou, Yun; Zhang, Xu; Chen, Guangfu

2012-11-01

The purpose of this study was to evaluate the effectiveness of three-dimensional contrast-enhanced ultrasound in differentiating invasive and noninvasive neoplasms of urinary bladder. A total of 60 lesions in 60 consecutive patients with bladder tumors received three dimensional ultrasonography, low acoustic power contrast enhanced ultrasonography and low acoustic power three-dimensional contrast-enhanced ultrasound examination. The IU22 ultrasound scanner and a volume transducer were used and the ultrasound contrast agent was SonoVue. The contrast-specific sonographic imaging modes were PI (pulse inversion) and PM (power modulation). The three dimensional ultrasonography, contrast enhanced ultrasonography, and three-dimensional contrast-enhanced ultrasound images were independently reviewed by two readers who were not in the images acquisition. Images were analyzed off-site. A level of confidence in the diagnosis of tumor invasion of the muscle layer was assigned on a 5° scale. Receiver operating characteristic analysis was used to assess overall confidence in the diagnosis of muscle invasion by tumor. Kappa values were used to assess inter-readers agreement. Histologic diagnosis was obtained for all patients. Final pathologic staging revealed 44 noninvasive tumors and 16 invasive tumors. Three-dimensional contrast-enhanced ultrasound depicted all 16 muscle-invasive tumors. The diagnostic performance of three-dimensional contrast-enhanced ultrasound was better than those of three dimensional ultrasonography and contrast enhanced ultrasonography. The receiver operating characteristic curves were 0.976 and 0.967 for three-dimensional contrast-enhanced ultrasound, those for three dimensional ultrasonography were 0.881 and 0.869, those for contrast enhanced ultrasonography were 0.927 and 0.929. The kappa values in the three dimensional ultrasonography, contrast enhanced ultrasonography and three-dimensional contrast-enhanced ultrasound for inter-reader agreements were 0.717, 0.794 and 0.914. Three-dimensional contrast-enhanced ultrasound imaging, with contrast-enhanced spatial visualization is clinical useful for differentiating invasive and noninvasive neoplasms of urinary bladder objectively. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Multiple object, three-dimensional motion tracking using the Xbox Kinect sensor

NASA Astrophysics Data System (ADS)

Rosi, T.; Onorato, P.; Oss, S.

2017-11-01

In this article we discuss the capability of the Xbox Kinect sensor to acquire three-dimensional motion data of multiple objects. Two experiments regarding fundamental features of Newtonian mechanics are performed to test the tracking abilities of our setup. Particular attention is paid to check and visualise the conservation of linear momentum, angular momentum and energy. In both experiments, two objects are tracked while falling in the gravitational field. The obtained data is visualised in a 3D virtual environment to help students understand the physics behind the performed experiments. The proposed experiments were analysed with a group of university students who are aspirant physics and mathematics teachers. Their comments are presented in this paper.

The Hierarchical Brain Network for Face Recognition

PubMed Central

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282

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

PubMed

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

2016-10-15

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

Laboratory-size three-dimensional x-ray microscope with Wolter type I mirror optics and an electron-impact water window x-ray source

NASA Astrophysics Data System (ADS)

Ohsuka, Shinji; Ohba, Akira; Onoda, Shinobu; Nakamoto, Katsuhiro; Nakano, Tomoyasu; Miyoshi, Motosuke; Soda, Keita; Hamakubo, Takao

2014-09-01

We constructed a laboratory-size three-dimensional water window x-ray microscope that combines wide-field transmission x-ray microscopy with tomographic reconstruction techniques, and observed bio-medical samples to evaluate its applicability to life science research fields. It consists of a condenser and an objective grazing incidence Wolter type I mirror, an electron-impact type oxygen Kα x-ray source, and a back-illuminated CCD for x-ray imaging. A spatial resolution limit of around 1.0 line pairs per micrometer was obtained for two-dimensional transmission images, and 1-μm scale three-dimensional fine structures were resolved.

Laboratory-size three-dimensional x-ray microscope with Wolter type I mirror optics and an electron-impact water window x-ray source.

PubMed

Ohsuka, Shinji; Ohba, Akira; Onoda, Shinobu; Nakamoto, Katsuhiro; Nakano, Tomoyasu; Miyoshi, Motosuke; Soda, Keita; Hamakubo, Takao

2014-09-01

We constructed a laboratory-size three-dimensional water window x-ray microscope that combines wide-field transmission x-ray microscopy with tomographic reconstruction techniques, and observed bio-medical samples to evaluate its applicability to life science research fields. It consists of a condenser and an objective grazing incidence Wolter type I mirror, an electron-impact type oxygen Kα x-ray source, and a back-illuminated CCD for x-ray imaging. A spatial resolution limit of around 1.0 line pairs per micrometer was obtained for two-dimensional transmission images, and 1-μm scale three-dimensional fine structures were resolved.

The Use of Geometry Learning Media Based on Augmented Reality for Junior High School Students

NASA Astrophysics Data System (ADS)

Rohendi, D.; Septian, S.; Sutarno, H.

2018-02-01

Understanding the geometry especially of three-dimensional space is still considered difficult by some students. Therefore, a learning innovation is required to overcome students’ difficulties in learning geometry. In this research, we developed geometry learning media based on augmented reality in android flatform’s then it was implemented in teaching three-dimensional objects for some junior high school students to find out: how is the students response in using this new media in geometry and is this media can solve the student’s difficulties in understanding geometry concept. The results showed that the use of geometry learning media based on augmented reality in android flatform is able to get positive responses from the students in learning geometry concepts especially three-dimensional objects and students more easy to understand concept of diagonal in geometry than before using this media.

Differing time dependencies of object recognition memory impairments produced by nicotinic and muscarinic cholinergic antagonism in perirhinal cortex

PubMed Central

Tinsley, Chris J.; Fontaine-Palmer, Nadine S.; Vincent, Maria; Endean, Emma P.E.; Aggleton, John P.; Brown, Malcolm W.; Warburton, E. Clea

2011-01-01

The roles of muscarinic and nicotinic cholinergic receptors in perirhinal cortex in object recognition memory were compared. Rats' discrimination of a novel object preference test (NOP) test was measured after either systemic or local infusion into the perirhinal cortex of the nicotinic receptor antagonist methyllycaconitine (MLA), which targets alpha-7 (α7) amongst other nicotinic receptors or the muscarinic receptor antagonists scopolamine, AFDX-384, and pirenzepine. Methyllycaconitine administered systemically or intraperirhinally before acquisition impaired recognition memory tested after a 24-h, but not a 20-min delay. In contrast, all three muscarinic antagonists produced a similar, unusual pattern of impairment with amnesia after a 20-min delay, but remembrance after a 24-h delay. Thus, the amnesic effects of nicotinic and muscarinic antagonism were doubly dissociated across the 20-min and 24-h delays. The same pattern of shorter-term but not longer-term memory impairment was found for scopolamine whether the object preference test was carried out in a square arena or a Y-maze and whether rats of the Dark Agouti or Lister-hooded strains were used. Coinfusion of MLA and either scopolamine or AFDX-384 produced an impairment profile matching that for MLA. Hence, the antagonists did not act additively when coadministered. These findings establish an important role in recognition memory for both nicotinic and muscarinic cholinergic receptors in perirhinal cortex, and provide a challenge to simple ideas about the role of cholinergic processes in recognition memory: The effects of muscarinic and nicotinic antagonism are neither independent nor additive. PMID:21693636

Differing time dependencies of object recognition memory impairments produced by nicotinic and muscarinic cholinergic antagonism in perirhinal cortex.

PubMed

Tinsley, Chris J; Fontaine-Palmer, Nadine S; Vincent, Maria; Endean, Emma P E; Aggleton, John P; Brown, Malcolm W; Warburton, E Clea

2011-01-01

The roles of muscarinic and nicotinic cholinergic receptors in perirhinal cortex in object recognition memory were compared. Rats' discrimination of a novel object preference test (NOP) test was measured after either systemic or local infusion into the perirhinal cortex of the nicotinic receptor antagonist methyllycaconitine (MLA), which targets alpha-7 (α7) amongst other nicotinic receptors or the muscarinic receptor antagonists scopolamine, AFDX-384, and pirenzepine. Methyllycaconitine administered systemically or intraperirhinally before acquisition impaired recognition memory tested after a 24-h, but not a 20-min delay. In contrast, all three muscarinic antagonists produced a similar, unusual pattern of impairment with amnesia after a 20-min delay, but remembrance after a 24-h delay. Thus, the amnesic effects of nicotinic and muscarinic antagonism were doubly dissociated across the 20-min and 24-h delays. The same pattern of shorter-term but not longer-term memory impairment was found for scopolamine whether the object preference test was carried out in a square arena or a Y-maze and whether rats of the Dark Agouti or Lister-hooded strains were used. Coinfusion of MLA and either scopolamine or AFDX-384 produced an impairment profile matching that for MLA. Hence, the antagonists did not act additively when coadministered. These findings establish an important role in recognition memory for both nicotinic and muscarinic cholinergic receptors in perirhinal cortex, and provide a challenge to simple ideas about the role of cholinergic processes in recognition memory: The effects of muscarinic and nicotinic antagonism are neither independent nor additive.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

DORSAL HIPPOCAMPAL PROGESTERONE INFUSIONS ENHANCE OBJECT RECOGNITION IN YOUNG FEMALE MICE

PubMed Central

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

2009-01-01

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

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

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.

An Interactive Augmented Reality Implementation of Hijaiyah Alphabet for Children Education

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Akbar, F.; Syahputra, M. F.; Budiman, M. A.; Hizriadi, A.

2018-03-01

Hijaiyah alphabet is letters used in the Qur’an. An attractive and exciting learning process of Hijaiyah alphabet is necessary for the children. One of the alternatives to create attractive and interesting learning process of Hijaiyah alphabet is to develop it into a mobile application using augmented reality technology. Augmented reality is a technology that combines two-dimensional or three-dimensional virtual objects into actual three-dimensional circles and projects them in real time. The purpose of application aims to foster the children interest in learning Hijaiyah alphabet. This application is using Smartphone and marker as the medium. It was built using Unity and augmented reality library, namely Vuforia, then using Blender as the 3D object modeling software. The output generated from this research is the learning application of Hijaiyah letters using augmented reality. How to use it is as follows: first, place marker that has been registered and printed; second, the smartphone camera will track the marker. If the marker is invalid, the user should repeat the tracking process. If the marker is valid and identified, the marker will have projected the objects of Hijaiyah alphabet in three-dimensional form. Lastly, the user can learn and understand the shape and pronunciation of Hijaiyah alphabet by touching the virtual button on the marker

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

PubMed Central

Janko, Vito

2017-01-01

The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301

3-D vision and figure-ground separation by visual cortex.

PubMed

Grossberg, S

1994-01-01

A neural network theory of three-dimensional (3-D) vision, called FACADE theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a boundary contour system (BCS) and a feature contour system (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that are mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object parts are separated, completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, Da Vinci stereopsis, 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analyzed. The BCS and FCS subsystems model aspects of how the two parvocellular cortical processing streams that join the lateral geniculate nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-DEpth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact with cortical mechanisms of spatial attention, attentive object learning, and visual search. Adaptive resonance theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal (IT) cortex for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular motion BCS signals interact with the model Where stream.(ABSTRACT TRUNCATED AT 400 WORDS)

Three-dimensional displays and stereo vision

PubMed Central

Westheimer, Gerald

2011-01-01

Procedures for three-dimensional image reconstruction that are based on the optical and neural apparatus of human stereoscopic vision have to be designed to work in conjunction with it. The principal methods of implementing stereo displays are described. Properties of the human visual system are outlined as they relate to depth discrimination capabilities and achieving optimal performance in stereo tasks. The concept of depth rendition is introduced to define the change in the parameters of three-dimensional configurations for cases in which the physical disposition of the stereo camera with respect to the viewed object differs from that of the observer's eyes. PMID:21490023

Doppler-Only Synthetic Aperture Radar

DTIC Science & Technology

2006-12-01

5 B. TARGET RECOGNITION TECHNIQUES .................................................6 1. Cooperative Targets...6 3. Techniques ............................................................................................6 C. TARGET RECOGNITION...3. Implementation of High Range Resolution Techniques .................12 F. TWO-DIMENSIONAL IMAGING

Medical information security in the era of artificial intelligence.

PubMed

Wang, Yufeng; Wang, Liwei; Xue, Chang-Ao

2018-06-01

In recent years, biometric technologies, such as iris, facial, and finger vein recognition, have reached consumers and are being increasingly applied. However, it remains unknown whether these highly specific biometric technologies are as safe as declared by their manufacturers. As three-dimensional (3D) reconstruction based on medical imaging and 3D printing are being developed, these biometric technologies may face severe challenges. Copyright © 2018 Elsevier Ltd. All rights reserved.

Corkscrew point spread function for far-field three-dimensional nanoscale localization of pointlike objects

PubMed Central

Lew, Matthew D.; Lee, Steven F.; Badieirostami, Majid; Moerner, W. E.

2011-01-01

We describe the corkscrew point spread function (PSF), which can localize objects in three dimensions throughout a 3.2 µm depth of field with nanometer precision. The corkscrew PSF rotates as a function of the axial (z) position of an emitter. Fisher information calculations show that the corkscrew PSF can achieve nanometer localization precision with limited numbers of photons. We demonstrate three-dimensional super-resolution microscopy with the corkscrew PSF by imaging beads on the surface of a triangular polydimethylsiloxane (PDMS) grating. With 99,000 photons detected, the corkscrew PSF achieves a localization precision of 2.7 nm in x, 2.1 nm in y, and 5.7 nm in z. PMID:21263500

Corkscrew point spread function for far-field three-dimensional nanoscale localization of pointlike objects.

PubMed

Lew, Matthew D; Lee, Steven F; Badieirostami, Majid; Moerner, W E

2011-01-15

We describe the corkscrew point spread function (PSF), which can localize objects in three dimensions throughout a 3.2 μm depth of field with nanometer precision. The corkscrew PSF rotates as a function of the axial (z) position of an emitter. Fisher information calculations show that the corkscrew PSF can achieve nanometer localization precision with limited numbers of photons. We demonstrate three-dimensional super-resolution microscopy with the corkscrew PSF by imaging beads on the surface of a triangular polydimethylsiloxane (PDMS) grating. With 99,000 photons detected, the corkscrew PSF achieves a localization precision of 2.7 nm in x, 2.1 nm in y, and 5.7 nm in z.

Robust kernel collaborative representation for face recognition

NASA Astrophysics Data System (ADS)

Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

2015-05-01

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

Three-dimensional tracking and imaging laser scanner for space operations

NASA Astrophysics Data System (ADS)

Laurin, Denis G.; Beraldin, J. A.; Blais, Francois; Rioux, Marc; Cournoyer, Luc

1999-05-01

This paper presents the development of a laser range scanner (LARS) as a three-dimensional sensor for space applications. The scanner is a versatile system capable of doing surface imaging, target ranging and tracking. It is capable of short range (0.5 m to 20 m) and long range (20 m to 10 km) sensing using triangulation and time-of-flight (TOF) methods respectively. At short range (1 m), the resolution is sub-millimeter and drops gradually with distance (2 cm at 10 m). For long range, the TOF provides a constant resolution of plus or minus 3 cm, independent of range. The LARS could complement the existing Canadian Space Vision System (CSVS) for robotic manipulation. As an active vision system, the LARS is immune to sunlight and adverse lighting; this is a major advantage over the CSVS, as outlined in this paper. The LARS could also replace existing radar systems used for rendezvous and docking. There are clear advantages of an optical system over a microwave radar in terms of size, mass, power and precision. Equipped with two high-speed galvanometers, the laser can be steered to address any point in a 30 degree X 30 degree field of view. The scanning can be continuous (raster scan, Lissajous) or direct (random). This gives the scanner the ability to register high-resolution 3D images of range and intensity (up to 4000 X 4000 pixels) and to perform point target tracking as well as object recognition and geometrical tracking. The imaging capability of the scanner using an eye-safe laser is demonstrated. An efficient fiber laser delivers 60 mW of CW or 3 (mu) J pulses at 20 kHz for TOF operation. Implementation of search and track of multiple targets is also demonstrated. For a single target, refresh rates up to 137 Hz is possible. Considerations for space qualification of the scanner are discussed. Typical space operations, such as docking, object attitude tracking, and inspections are described.

Recognition-induced forgetting is not due to category-based set size.

PubMed

Maxcey, Ashleigh M

2016-01-01

What are the consequences of accessing a visual long-term memory representation? Previous work has shown that accessing a long-term memory representation via retrieval improves memory for the targeted item and hurts memory for related items, a phenomenon called retrieval-induced forgetting. Recently we found a similar forgetting phenomenon with recognition of visual objects. Recognition-induced forgetting occurs when practice recognizing an object during a two-alternative forced-choice task, from a group of objects learned at the same time, leads to worse memory for objects from that group that were not practiced. An alternative explanation of this effect is that category-based set size is inducing forgetting, not recognition practice as claimed by some researchers. This alternative explanation is possible because during recognition practice subjects make old-new judgments in a two-alternative forced-choice task, and are thus exposed to more objects from practiced categories, potentially inducing forgetting due to set-size. Herein I pitted the category-based set size hypothesis against the recognition-induced forgetting hypothesis. To this end, I parametrically manipulated the amount of practice objects received in the recognition-induced forgetting paradigm. If forgetting is due to category-based set size, then the magnitude of forgetting of related objects will increase as the number of practice trials increases. If forgetting is recognition induced, the set size of exemplars from any given category should not be predictive of memory for practiced objects. Consistent with this latter hypothesis, additional practice systematically improved memory for practiced objects, but did not systematically affect forgetting of related objects. These results firmly establish that recognition practice induces forgetting of related memories. Future directions and important real-world applications of using recognition to access our visual memories of previously encountered objects are discussed.

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

A three-dimensional bucking system for optimal bucking of Central Appalachian hardwoods

Treesearch

Jingxin Wang; Jingang Liu; Chris B. LeDoux

2009-01-01

An optimal tree stembucking systemwas developed for central Appalachian hardwood species using three-dimensional (3D) modeling techniques. ActiveX Data Objects were implemented via MS Visual C++/OpenGL to manipulate tree data which were supported by a backend relational data model with five data entity types for stems, grades and prices, logs, defects, and stem shapes...

Efficient live face detection to counter spoof attack in face recognition systems

NASA Astrophysics Data System (ADS)

Biswas, Bikram Kumar; Alam, Mohammad S.

2015-03-01

Face recognition is a critical tool used in almost all major biometrics based security systems. But recognition, authentication and liveness detection of the face of an actual user is a major challenge because an imposter or a non-live face of the actual user can be used to spoof the security system. In this research, a robust technique is proposed which detects liveness of faces in order to counter spoof attacks. The proposed technique uses a three-dimensional (3D) fast Fourier transform to compare spectral energies of a live face and a fake face in a mathematically selective manner. The mathematical model involves evaluation of energies of selective high frequency bands of average power spectra of both live and non-live faces. It also carries out proper recognition and authentication of the face of the actual user using the fringe-adjusted joint transform correlation technique, which has been found to yield the highest correlation output for a match. Experimental tests show that the proposed technique yields excellent results for identifying live faces.

Usage of stereoscopic visualization in the learning contents of rotational motion.

PubMed

Matsuura, Shu

2013-01-01

Rotational motion plays an essential role in physics even at an introductory level. In addition, the stereoscopic display of three-dimensional graphics includes is advantageous for the presentation of rotational motions, particularly for depth recognition. However, the immersive visualization of rotational motion has been known to lead to dizziness and even nausea for some viewers. Therefore, the purpose of this study is to examine the onset of nausea and visual fatigue when learning rotational motion through the use of a stereoscopic display. The findings show that an instruction method with intermittent exposure of the stereoscopic display and a simplification of its visual components reduced the onset of nausea and visual fatigue for the viewers, which maintained the overall effect of instantaneous spatial recognition.

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

PubMed

Purpura, Giulia; Cioni, Giovanni; Tinelli, Francesca

2018-07-01

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

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

PubMed

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

2015-09-01

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

Adding the Third Dimension to Virus Life Cycles: Three-Dimensional Reconstruction of Icosahedral Viruses from Cryo-Electron Micrographs

PubMed Central

Baker, T. S.; Olson, N. H.; Fuller, S. D.

1999-01-01

Viruses are cellular parasites. The linkage between viral and host functions makes the study of a viral life cycle an important key to cellular functions. A deeper understanding of many aspects of viral life cycles has emerged from coordinated molecular and structural studies carried out with a wide range of viral pathogens. Structural studies of viruses by means of cryo-electron microscopy and three-dimensional image reconstruction methods have grown explosively in the last decade. Here we review the use of cryo-electron microscopy for the determination of the structures of a number of icosahedral viruses. These studies span more than 20 virus families. Representative examples illustrate the use of moderate- to low-resolution (7- to 35-Å) structural analyses to illuminate functional aspects of viral life cycles including host recognition, viral attachment, entry, genome release, viral transcription, translation, proassembly, maturation, release, and transmission, as well as mechanisms of host defense. The success of cryo-electron microscopy in combination with three-dimensional image reconstruction for icosahedral viruses provides a firm foundation for future explorations of more-complex viral pathogens, including the vast number that are nonspherical or nonsymmetrical. PMID:10585969

The Role of Perceptual Load in Object Recognition

ERIC Educational Resources Information Center

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

2009-01-01

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

Color Constancy in Two-Dimensional and Three-Dimensional Scenes: Effects of Viewing Methods and Surface Texture

PubMed Central

Morimoto, Takuma; Mizokami, Yoko; Yaguchi, Hirohisa; Buck, Steven L.

2017-01-01

There has been debate about how and why color constancy may be better in three-dimensional (3-D) scenes than in two-dimensional (2-D) scenes. Although some studies have shown better color constancy for 3-D conditions, the role of specific cues remains unclear. In this study, we compared color constancy for a 3-D miniature room (a real scene consisting of actual objects) and 2-D still images of that room presented on a monitor using three viewing methods: binocular viewing, monocular viewing, and head movement. We found that color constancy was better for the 3-D room; however, color constancy for the 2-D image improved when the viewing method caused the scene to be perceived more like a 3-D scene. Separate measurements of the perceptual 3-D effect of each viewing method also supported these results. An additional experiment comparing a miniature room and its image with and without texture suggested that surface texture of scene objects contributes to color constancy. PMID:29238513

Docking alignment system

NASA Technical Reports Server (NTRS)

Monford, Leo G. (Inventor)

1990-01-01

Improved techniques are provided for alignment of two objects. The present invention is particularly suited for three-dimensional translation and three-dimensional rotational alignment of objects in outer space. A camera 18 is fixedly mounted to one object, such as a remote manipulator arm 10 of the spacecraft, while the planar reflective surface 30 is fixed to the other object, such as a grapple fixture 20. A monitor 50 displays in real-time images from the camera, such that the monitor displays both the reflected image of the camera and visible markings on the planar reflective surface when the objects are in proper alignment. The monitor may thus be viewed by the operator and the arm 10 manipulated so that the reflective surface is perpendicular to the optical axis of the camera, the roll of the reflective surface is at a selected angle with respect to the camera, and the camera is spaced a pre-selected distance from the reflective surface.

How Category Structure Influences the Perception of Object Similarity: The Atypicality Bias

PubMed Central

Tanaka, James William; Kantner, Justin; Bartlett, Marni

2011-01-01

Why do some faces appear more similar than others? Beyond structural factors, we speculate that similarity is governed by the organization of faces located in a multi-dimensional face space. To test this hypothesis, we morphed a typical face with an atypical face. If similarity judgments are guided purely by their physical properties, the morph should be perceived to be equally similar to its typical parent as its atypical parent. However, contrary to the structural prediction, our results showed that the morph face was perceived to be more similar to the atypical face than the typical face. Our empirical studies show that the atypicality bias is not limited to faces, but extends to other object categories (birds) whose members share common shape properties. We also demonstrate atypicality bias is malleable and can change subject to category learning and experience. Collectively, the empirical evidence indicates that perceptions of face and object similarity are affected by the distribution of stimuli in a face or object space. In this framework, atypical stimuli are located in a sparser region of the space where there is less competition for recognition and therefore, these representations capture a broader range of inputs. In contrast, typical stimuli are located in a denser region of category space where there is increased competition for recognition and hence, these representation draw a more restricted range of face inputs. These results suggest that the perceived likeness of an object is influenced by the organization of surrounding exemplars in the category space. PMID:22685441

Three-dimensional echocardiography of congenital abnormalities of the left atrioventricular valve.

PubMed

Rice, Kathryn; Simpson, John

2015-03-01

Congenital abnormalities of the left atrioventricular (AV) valve are a significant diagnostic challenge. Traditionally, reliance has been placed on two-dimensional echocardiographic (2DE) imaging to guide recognition of the specific morphological features. Real-time 3DE can provide unique views of the left AV valve with the potential to improve understanding of valve morphology and function to facilitate surgical planning. This review illustrates the features of congenital abnormalities of the left AV valve assessed by 3DE. The similarities and differences in morphology between different lesions are described, both with respect to the valve itself and supporting chordal apparatus. The potential advantages as well as limitations of this technique in clinical practice are outlined.

Prediction of glycolipid-binding domains from the amino acid sequence of lipid raft-associated proteins: application to HpaA, a protein involved in the adhesion of Helicobacter pylori to gastrointestinal cells.

PubMed

Fantini, Jacques; Garmy, Nicolas; Yahi, Nouara

2006-09-12

Protein-glycolipid interactions mediate the attachment of various pathogens to the host cell surface as well as the association of numerous cellular proteins with lipid rafts. Thus, it is of primary importance to identify the protein domains involved in glycolipid recognition. Using structure similarity searches, we could identify a common glycolipid-binding domain in the three-dimensional structure of several proteins known to interact with lipid rafts. Yet the three-dimensional structure of most raft-targeted proteins is still unknown. In the present study, we have identified a glycolipid-binding domain in the amino acid sequence of a bacterial adhesin (Helicobacter pylori adhesin A, HpaA). The prediction was based on the major properties of the glycolipid-binding domains previously characterized by structural searches. A short (15-mer) synthetic peptide corresponding to this putative glycolipid-binding domain was synthesized, and we studied its interaction with glycolipid monolayers at the air-water interface. The synthetic HpaA peptide recognized LacCer but not Gb3. This glycolipid specificity was in line with that of the whole bacterium. Molecular modeling studies gave some insights into this high selectivity of interaction. It also suggested that Phe147 in HpaA played a key role in LacCer recognition, through sugar-aromatic CH-pi stacking interactions with the hydrophobic side of the galactose ring of LacCer. Correspondingly, the replacement of Phe147 with Ala strongly affected LacCer recognition, whereas substitution with Trp did not. Our method could be used to identify glycolipid-binding domains in microbial and cellular proteins interacting with lipid shells, rafts, and other specialized membrane microdomains.

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Recognition of upper airway and surrounding structures at MRI in pediatric PCOS and OSAS

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, J. K.; Odhner, D.; Sin, Sanghun; Arens, Raanan

2013-03-01

Obstructive Sleep Apnea Syndrome (OSAS) is common in obese children with risk being 4.5 fold compared to normal control subjects. Polycystic Ovary Syndrome (PCOS) has recently been shown to be associated with OSAS that may further lead to significant cardiovascular and neuro-cognitive deficits. We are investigating image-based biomarkers to understand the architectural and dynamic changes in the upper airway and the surrounding hard and soft tissue structures via MRI in obese teenage children to study OSAS. At the previous SPIE conferences, we presented methods underlying Fuzzy Object Models (FOMs) for Automatic Anatomy Recognition (AAR) based on CT images of the thorax and the abdomen. The purpose of this paper is to demonstrate that the AAR approach is applicable to a different body region and image modality combination, namely in the study of upper airway structures via MRI. FOMs were built hierarchically, the smaller sub-objects forming the offspring of larger parent objects. FOMs encode the uncertainty and variability present in the form and relationships among the objects over a study population. Totally 11 basic objects (17 including composite) were modeled. Automatic recognition for the best pose of FOMs in a given image was implemented by using four methods - a one-shot method that does not require search, another three searching methods that include Fisher Linear Discriminate (FLD), a b-scale energy optimization strategy, and optimum threshold recognition method. In all, 30 multi-fold cross validation experiments based on 15 patient MRI data sets were carried out to assess the accuracy of recognition. The results indicate that the objects can be recognized with an average location error of less than 5 mm or 2-3 voxels. Then the iterative relative fuzzy connectedness (IRFC) algorithm was adopted for delineation of the target organs based on the recognized results. The delineation results showed an overall FP and TP volume fraction of 0.02 and 0.93.

Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

NASA Astrophysics Data System (ADS)

Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

2014-09-01

Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

Impedance Eduction in Sound Fields With Peripherally Varying Liners and Flow

NASA Technical Reports Server (NTRS)

Watson, W. R.; Jones, M. G.

2015-01-01

A two-dimensional impedance eduction theory is extended to three-dimensional sound fields and peripherally varying duct liners. The approach is to first measure the acoustic pressure field at a series of flush-mounted wall microphones located around the periphery of the flow duct. The numerical solution for the acoustic pressure field at these microphones is also obtained by solving the three-dimensional convected Helmholtz equation using the finite element method. A quadratic objective function based on the difference between the measured and finite element solution is constructed and the unknown impedance function is obtained by minimizing this objective function. Impedance spectra educed for two uniform-structure liners (a wire-mesh and a conventional liner) and a hard-soft-hard peripherally varying liner (for which the soft segment is that of the conventional liner) are presented. Results are presented at three mean flow Mach numbers and fourteen sound source frequencies. The impedance spectra of the uniform-structure liners are also computed using a two-dimensional impedance eduction theory. The primary conclusions of the study are: 1) when measured data is used with the uniform-structure liners, the three-dimensional theory reproduces the same impedance spectra as the two-dimensional theory except for frequencies corresponding to very low or very high liner attenuation; and 2) good agreement between the educed impedance spectra of the uniform structure conventional liner and the soft segment of the peripherally varying liner is obtained.

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

Generalized three-dimensional experimental lightning code (G3DXL) user's manual

NASA Technical Reports Server (NTRS)

Kunz, Karl S.

1986-01-01

Information concerning the programming, maintenance and operation of the G3DXL computer program is presented and the theoretical basis for the code is described. The program computes time domain scattering fields and surface currents and charges induced by a driving function on and within a complex scattering object which may be perfectly conducting or a lossy dielectric. This is accomplished by modeling the object with cells within a three-dimensional, rectangular problem space, enforcing the appropriate boundary conditions and differencing Maxwell's equations in time. In the present version of the program, the driving function can be either the field radiated by a lightning strike or a direct lightning strike. The F-106 B aircraft is used as an example scattering object.

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

PubMed

Yamashita, Wakayo; Wang, Gang; Tanaka, Keiji

2010-01-01

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

Review and comparison of non-conventional imaging systems for three-dimensional digitization of transparent objects

NASA Astrophysics Data System (ADS)

Mériaudeau, Fabrice; Rantoson, Rindra; Fofi, David; Stolz, Christophe

2012-04-01

Fashion and design greatly influence the conception of manufactured products which now exhibit complex forms and shapes. Two-dimensional quality control procedures (e.g., shape, textures, colors, and 2D geometry) are progressively being replaced by 3D inspection methods (e.g., 3D geometry, colors, and texture on the 3D shape) therefore requiring a digitization of the object surface. Three dimensional surface acquisition is a topic which has been studied to a large extent, and a significant number of techniques for acquiring 3D shapes has been proposed, leading to a wide range of commercial solutions available on the market. These systems cover a wide range from micro-scale objects such as shape from focus and shape from defocus techniques, to several meter sized objects (time of flight technique). Nevertheless, the use of such systems still encounters difficulties when dealing with non-diffuse (non Lambertian) surfaces as is the case for transparent, semi-transparent, or highly reflective materials (e.g., glass, crystals, plastics, and shiny metals). We review and compare various systems and approaches which were recently developed for 3D digitization of transparent objects.

Three-Dimensional Computer Simulation as an Important Competence Based Aspect of a Modern Mining Professional

NASA Astrophysics Data System (ADS)

Aksenova, Olesya; Pachkina, Anna

2017-11-01

The article deals with the problem of necessity of educational process transformation to meet the requirements of modern miming industry; cooperative developing of new educational programs and implementation of educational process taking into account modern manufacturability. The paper proves the idea of introduction into mining professionals learning process studying of three-dimensional models of surface technological complex, ore reserves and underground digging complex as well as creating these models in different graphic editors and working with the information analysis model obtained on the basis of these three-dimensional models. The technological process of manless coal mining at the premises of the mine Polysaevskaya controlled by the information analysis models built on the basis of three-dimensional models of individual objects and technological process as a whole, and at the same time requiring the staff able to use the programs of three-dimensional positioning in the miners and equipment global frame of reference is covered.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

Fine Metal Mask 3-Dimensional Measurement by using Scanning Digital Holographic Microscope

NASA Astrophysics Data System (ADS)

Shin, Sanghoon; Yu, Younghun

2018-04-01

For three-dimensional microscopy, fast and high axial resolution are very important. Extending the depth of field for digital holographic is necessary for three-dimensional measurements of thick samples. We propose an optical sectioning method for optical scanning digital holography that is performed in the frequency domain by spatial filtering of a reconstructed amplitude image. We established a scanning dual-wavelength off-axis digital holographic microscope to measure samples that exhibit a large amount of coherent noise and a thickness larger than the depth of focus of the objective lens. As a demonstration, we performed a three-dimensional measurement of a fine metal mask with a reconstructed sectional phase image and filtering with a reconstructed amplitude image.

Collaborative activity between parietal and dorso-lateral prefrontal cortex in dynamic spatial working memory revealed by fMRI.

PubMed

Diwadkar, V A; Carpenter, P A; Just, M A

2000-07-01

Functional MRI was used to determine how the constituents of the cortical network subserving dynamic spatial working memory respond to two types of increases in task complexity. Participants mentally maintained the most recent location of either one or three objects as the three objects moved discretely in either a two- or three-dimensional array. Cortical activation in the dorsolateral prefrontal (DLPFC) and the parietal cortex increased as a function of the number of object locations to be maintained and the dimensionality of the display. An analysis of the response characteristics of the individual voxels showed that a large proportion were activated only when both the variables imposed the higher level of demand. A smaller proportion were activated specifically in response to increases in task demand associated with each of the independent variables. A second experiment revealed the same effect of dimensionality in the parietal cortex when the movement of objects was signaled auditorily rather than visually, indicating that the additional representational demands induced by 3-D space are independent of input modality. The comodulation of activation in the prefrontal and parietal areas by the amount of computational demand suggests that the collaboration between areas is a basic feature underlying much of the functionality of spatial working memory. Copyright 2000 Academic Press.

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

PubMed Central

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-01-01

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

Application of an object-oriented programming paradigm in three-dimensional computer modeling of mechanically active gastrointestinal tissues.

PubMed

Rashev, P Z; Mintchev, M P; Bowes, K L

2000-09-01

The aim of this study was to develop a novel three-dimensional (3-D) object-oriented modeling approach incorporating knowledge of the anatomy, electrophysiology, and mechanics of externally stimulated excitable gastrointestinal (GI) tissues and emphasizing the "stimulus-response" principle of extracting the modeling parameters. The modeling method used clusters of class hierarchies representing GI tissues from three perspectives: 1) anatomical; 2) electrophysiological; and 3) mechanical. We elaborated on the first four phases of the object-oriented system development life-cycle: 1) analysis; 2) design; 3) implementation; and 4) testing. Generalized cylinders were used for the implementation of 3-D tissue objects modeling the cecum, the descending colon, and the colonic circular smooth muscle tissue. The model was tested using external neural electrical tissue excitation of the descending colon with virtual implanted electrodes and the stimulating current density distributions over the modeled surfaces were calculated. Finally, the tissue deformations invoked by electrical stimulation were estimated and represented by a mesh-surface visualization technique.

Natural User Interface Sensors for Human Body Measurement

NASA Astrophysics Data System (ADS)

Boehm, J.

2012-08-01

The recent push for natural user interfaces (NUI) in the entertainment and gaming industry has ushered in a new era of low cost three-dimensional sensors. While the basic idea of using a three-dimensional sensor for human gesture recognition dates some years back it is not until recently that such sensors became available on the mass market. The current market leader is PrimeSense who provide their technology for the Microsoft Xbox Kinect. Since these sensors are developed to detect and observe human users they should be ideally suited to measure the human body. We describe the technology of a line of NUI sensors and assess their performance in terms of repeatability and accuracy. We demonstrate the implementation of a prototype scanner integrating several NUI sensors to achieve full body coverage. We present the results of the obtained surface model of a human body.