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检索条件"任意字段=2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013"

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Class-Based Matching of Object Parts

Class-Based Matching of Object Parts

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： E. Bart S. Ullman Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel

We develop a novel technique for class-based matching of object parts across large changes in viewing conditions. Given a set of images of objects from a given class under different viewing conditions, the algorithm identifies corresponding regions depicting the same object part in different images. The technique is based on using the equivalence of corresponding features in different viewing conditions. This equivalence-based matching scheme is not restricted to planar components or affine transformations. As a result, it identifies corresponding parts more accurately and under more general conditions than previous methods. The scheme is general and works for a variety of natural object classes. We demonstrate that using the proposed methods, a dense set of accurate correspondences can be obtained. Experimental comparisons to several known techniques are presented. An application to the problem of invariant object recognition is shown, and additional applications to wide-baseline stereo are discussed.

关键词： Object recognition Mouth computer vision Stereo vision computer science Mathematics Image recognition Eyes Nose Lighting

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Biologically-Inspired Face Detection: Non-Brute-Force-Search Approach

Biologically-Inspired Face Detection: Non-Brute-Force-Search...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： C. Siagian L. Itti Department of Computer Science University of Southern California Los Angeles CA USA

We present a biologically-inspired face detection system. The system applies notions such as saliency, gist, and gaze to localize a face without performing blind spatial search. The saliency model consists of highly parallel low-level computations that operate in domains such as intensity, orientation, and color. It is used to direct attention to a set of conspicuous locations in an image as starting points. The gist model, computed in parallel with the saliency model, estimates holistic image characteristics such as dominant contours and magnitude in high and low spatial frequency bands. We are limiting its use to predicting the likely head size based on the entire scene. Also, instead of identifying face as a single entity, this system performs detection by parts and uses spatial configuration constraints to be robust against occlusion and perspective.

关键词： Face detection Layout Concurrent computing Humans computer science Frequency estimation Head Face recognition Biology Biological system modeling

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Direct Image Matching by Dynamic Warping

Direct Image Matching by Dynamic Warping

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Hansheng Lei V. Govindaraju CUBS Center for Unified Biometrics and Sensors State University of New York Amherst NY USA

In this paper, a new and efficient 2DDW (2-dimensional Dynamic Warping ) algorithm for direct image matching is proposed. Similar to the 1-dimensional DTW (Dynamic Time Warping) for sequence matching and optimal alignment, the 2DDW is aimed to elastically matching images which may be not aligned well. However, finding the optimal alignment between two images has been proved to be NP-complete [Elastic image matching is np-complete]. Therefore, reasonable constrains are imposed on the warping to bring down the complexity, such as continuity and monotonicity. The best complexity for continuous and monotonic 2DDW so far was reported as O(N^2 9^N) in [An efficient two-dimensional warping algorithm]. Our algorithm also guarantees continuity and monotonicity and the complexity is only O(N^6).

关键词： Image matching Cost function pattern recognition Dynamic programming Venus Biometrics Image sensors Biosensors Heuristic algorithms Image sequence analysis

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Articulated Motion Modeling for Activity Analysis

Articulated Motion Modeling for Activity Analysis

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Jiang Gao R.T. Collins A.G. Hauptmann H.D. Wactlar School of Computer Science Carnegie Mellon University Pittsburgh PA USA

We propose an algorithm for articulated human motion segmentation that estimates parametric motions of body parts and segments images into moving regions accordingly. Our approach combines robust optical flow estimation, RANSAC, and region segmentation using color and Gaussian shape priors. This combination results in an algorithm that can robustly estimate and segment multiple motions, even for moving regions with small support and in low-resolution images. Based on the raw motion segmentation, consistent body motions are detected over time to characterize human activity. The effectiveness of this approach is demonstrated in a real scenario: characterizing dining activities of patients at a nursing home.

关键词： Motion analysis Image segmentation Image motion analysis Humans Motion segmentation computer vision Motion estimation Robustness Biological system modeling Nonlinear optics

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Gradual Transition Detection Using Average Frame Similarity

Gradual Transition Detection Using Average Frame Similarity

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： T. Volkmer S.M.M. Tahaghoghi H.E. Williams School of Computer Science and Information Technology RMIT University Melbourne Australia

Segmenting digital video into its constituent basic semantic entities, or shots, is an important step for effective management and retrieval of video data. Recent automated techniques for detecting transitions between shots are highly effective on abrupt transitions. However, automated detection of gradual transitions, and the precise determination of the corresponding start and end frames, remains problematic. In this paper, we present a gradual transition detection approach based on average frame similarity and adaptive thresholds. We report good detection results on the TREC video track collections - particularly for dissolves and fades - and very high accuracy in identifying transition boundaries. Our technique is a valuable new tool for transition detection.

关键词： Gunshot detection systems Humans Video compression computer science Information technology Australia Technology management Information retrieval Consumer products Machine assisted indexing

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Using Associative Memory Principles to Enhance Perceptual Ability of vision Systems

Using Associative Memory Principles to Enhance Perceptual Ab...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： D.O. Gorodnichy O.P. Gorodnichy National Research Council of Canada Institute for Information Technology Ottawa Canada Kiev State University of Information and Communication Technologies Kiev Ukraine

The so called associative thinking, which humans are known to perform on every day basis, is attributed to the fact that human brain memorizes information using the dynamical system made of interconnected neurons. Retrieval of information in such a system is accomplished in associative sense; starting from an arbitrary state, which might be an encoded representation of a visual image, the brain activity converges to another state, which is stable and which is what the brain remembers. In this paper we explore the possibility of using an associative memory for the purpose of enhancing the interactive capability of perceptual vision systems. By following the biological memory principles, we show how vision systems can be designed to recognize faces, facial gestures and orientations, using low-end video-cameras and little computational power. In doing that we use the public domain associative memory code.

关键词： Associative memory Machine vision Humans Brain Neurons Information retrieval Image retrieval Image converters Biological information theory Face recognition

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An Ontology for Video Event Representation

An Ontology for Video Event Representation

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： R. Nevatia J. Hobbs B. Bolles Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA USC Information Sciences Institute Marina del Rey CA USA SRI International Inc. Menlo Park CA USA

Representation and recognition of events in a video is important for a number of tasks such as video surveillance, video browsing and content based video indexing. This paper describes the results of a "Challenge Project on Video Event Taxonomy" sponsored by the Advanced Research and Development Activity (ARDA) of the U.S. Government in the summer and fall of 2003. The project brought together more than 30 researchers in computer vision and knowledge representation and representatives of the user community. It resulted in the development of a formal language for describing an ontology of events, which we call VERL (Video Event Representation Language) and a companion language called VEML (Video Event Markup Language) to annotate instances of the events described in VERL. This paper provides a summary of VERL and VEML as well as the considerations associated with the specific design choices.

关键词： Ontologies Video surveillance Indexing Taxonomy Research and development Government computer vision Knowledge representation Formal languages Markup languages

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Development of a Face recognition System on an Image Processing LSI Chip

Development of a Face Recognition System on an Image Process...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： T. Kozakaya H. Nakaia Multimedia Laboratory Corporate Research & Development Center Toshiba Corporation Kawasaki Kanagawa Japan

We present a real-time and high-precision face recognition system using an image processing LSI chip:Visconti[Visconti: Multi-VLIW Image recognition Processor]. The system is compact and operates at low power, making it suitable for many purposes, including home security and robot vision. The LSI includes three media processing modules and peripherals which are suitable for machine vision. Face recognition is based on the constrained mutual sub-space method (CMSM), implemented on the LSI and optimized to make the best use of the hardware features. The optimization consists of four different levels: instruction, data, task and algorithm. It shows possible implementation of face recognition with multi-core CPUs or other LSI chips. Experimental results show the system operates at 20 frames/sec and a recognition rate is 99.59% when a threshold value is set to 0.55; performance comparable to that of a state-of-the-art system.

关键词： Face recognition Image processing Large scale integration Real time systems Image recognition Power system security Robot vision systems Machine vision Subspace constraints Constraint optimization

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Medial Visual Fragments as an Intermediate Image Representation for Segmentation and Perceptual Grouping

Medial Visual Fragments as an Intermediate Image Representat...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： A. Tamrakar B.B. Kimia Division of Engineering Brown University Providence RI USA

We present a novel representation of images based on a decomposition into atomic patches which we call medial visual fragments and which is particularly suited for structural grouping. Specifically, we show that the medial axis/shock graph of a contour map partitions the image domain into non-overlapping regions, which together with the image information define the visual fragments. The main advantage of such a generic representation is that both contour and regional information are explicitly available so that in the presence of partial evidence and ambiguity in maps indicating edges and regional homogeneity, both aspects can be simultaneously used for perceptual grouping of fragments into a coherent whole. Grouping of visual fragments is represented as a set of canonical transformations of visual fragments, namely, the gap and loop transforms. The advantage of this representation in comparison to perceptual grouping using only contour continuity or region grouping is demonstrated on synthetic and realistic examples.

关键词： Image representation Image segmentation Electric shock Surface texture computer Society computer vision pattern recognition conferences Partitioning algorithms

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AdaTree: Boosting a Weak Classifier into a Decision Tree

AdaTree: Boosting a Weak Classifier into a Decision Tree

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： E. Grossmann Center for Visualization and Virtual Environments University of Kentucky Lexington KY USA

We present a boosting method that results in a decision tree rather than a fixed linear sequence of classifiers. An equally correct statement is that we present a tree-growing method whose performance can be analysed in the framework of Adaboost. We argue that Adaboost can be improved by presenting the input to a sequence of weak classifiers, each one tuned to the conditional probability determined by the output of previous weak classifiers. As a result, the final classifier has a tree structure, rather than being linear, thus the name "Adatree". One of the consequences of the tree structure is that different input data may have different processing time. Early experimentation shows a reduced computation cost with respect to Adaboost. One of our intended applications is real-time detection, where cascades of boosted detectors have recently become successful. The reduced computation cost of the proposed method shows some potential for being used directly in detection problems, without need of a cascade.

关键词： Boosting Classification tree analysis Decision trees computer Society computer vision pattern recognition conferences

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