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检索条件"任意字段=2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003"

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Support Vector Tracking

Support Vector Tracking

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Avidan MobilEye Vision Technologies Limited Jerusalem Israel

ISBN: (纸本)0769512720

Support Vector Tracking (SVT) integrates the Support Vector Machine (SVM) classifier into an optic-flow based tracker. Instead of minimizing an intensity difference function between successive frames, SVT maximizes the SVM classification score. To account for large motions between successive frames, we build pyramids from the support vectors and use a coarse-to-fine approach in the classification stage. We show results of using a homogeneous quadratic polynomial kernel-SVT for vehicle tracking in image sequences.

关键词： Support vector machines Support vector machine classification Vehicle detection Integrated optics Brightness Biomedical optical imaging Optical character recognition software Face detection Electronic mail Polynomials

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Robust super-resolution

Robust super-resolution

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Zomet A. Rav-Acha S. Peleg School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem Israel

ISBN: (纸本)0769512720

A robust approach for super-resolution is, presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion errors, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors. A robust median estimator is combined in an iterative process to achieve a super resolution algorithm. This process can increase resolution even in regions with outliers, where other super resolution methods actually degrade the image.

关键词： Image resolution Noise robustness High-resolution imaging Degradation Motion segmentation computer vision Vectors computer science Iterative algorithms Image reconstruction

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Efficient grouping under perspective skew

Efficient grouping under perspective skew

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Turina T. Tuytelaars L. Van Gool Computer Vision Group Swiss Federal Institute of Technology Zurich Switzerland ESAT VISICS Katholieke Universiteit Leuven Leuven Belgium

ISBN: (纸本)0769512720

We present an efficient grouping strategy for the detection of regular repetitions of planar (but not necessarily coplanar) patterns. At the heart of our system lie the fixed structures that typify the geometric transformations of the regularities. The approach unifies a number of grouping types that have traditionally been dealt with separately. It avoids the use of combinatorics in the search for pattern repetitions, through the combined use of invariants for hashing-based pattern matching on the one hand, and Hough transforms for the detection of the fixed structures on the other hand. In this paper we concentrate on planar homologies and elations in particular Results on real-world scenes demonstrate the performance of the approach.

关键词： Mirrors Layout Combinatorial mathematics pattern matching Heart Humans Ventilation Reflection pattern analysis Symmetric matrices

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recognition of human gaits

Recognition of human gaits

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Bissacco A. Chiuso Yi Ma S. Soatto Computer Science University of California Los Angeles Los Angeles CA USA Dipartimento di Elettronica e Informatica Universitá di Padova Padova Italy Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

ISBN: (纸本)0769512720

We pose the problem of recognizing different types of human gait in the space of dynamical systems where each gait is represented Established techniques are employed to track a kinematic model of a human body in motion, and the trajectories of the parameters are used to learn a representation of a dynamical system, which defines a gait. Various types of distance between models are then computed These computations are non trivial due to the fact that, even for the case of linear systems, the space of canonical realizations is not linear.

关键词： Humans Hidden Markov models Trajectory Linear systems computer science Tracking Kinematics Biological system modeling Legged locomotion Photometry

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Appearance-based object recognition using multiple views

Appearance-based object recognition using multiple views

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Selinger R.C. Nelson Department of Computer Science University of Rochester Rochester NY USA

ISBN: (纸本)0769512720

Object recognition from a single view fails when the available features are not sufficient to determine the identity of a single object, either because of similarity with another object or because of feature corruption due to clutter and occlusion. Active object recognition systems have addressed this problem successfully, but they require complicated systems with adjustable viewpoints that are not always available. In this paper we investigate the performance gain available by combining the results of a single view object recognition system applied to imagery obtained from multiple fixed cameras. In particular, we address performance in cluttered scenes with varying degrees of information about relative camera pose. We argue that a property common to many computer vision recognition systems, which we term a weak target error, is responsible for two interesting limitations of multi-view performance enhancement: the lack of significant improvement in systems whose single-view performance is weak, and the plateauing of performance improvement as additional multi-view constraints are added.

关键词： Object recognition Cameras Feature extraction Image databases Spatial databases Voting computer science Performance gain Layout Target recognition

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Metric self calibration from screw-transform manifolds

Metric self calibration from screw-transform manifolds

引用

conference on computer vision and pattern recognition (cvpr)

作者： R.A. Manning C.R. Dyer Department of Computer Sciences University of Wisconsin Madison WI USA

ISBN: (纸本)0769512720

This paper introduces a method for metric self-calibration that is based on a novel decomposition of the fundamental matrix between two views taken by a camera with fixed internal parameters. The method blends important advantages of the Kruppa constraints and the modulus constraint: it works directly from fundamental matrices and uses a reduced-parameter representation for stability. General properties of the new decomposition are also developed, including an intuitive interpretation of the three free parameters of internal calibration. The approach is demonstrated on both real and synthetic data.

关键词： Calibration Cameras Transmission line matrix methods Matrix decomposition Fasteners Layout Stability Equations Image motion analysis Coordinate measuring machines

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A confidence measure for boundary detection and object selection

A confidence measure for boundary detection and object selec...

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conference on computer vision and pattern recognition (cvpr)

作者： E.N. Mortensen W.A. Barrett Brigham Young University USA Oregon State University USA

ISBN: (纸本)0769512720

We introduce a confidence measure that estimates the assurance that a graph arc (or edge) corresponds to an object boundary in an image. A weighted, planar graph is imposed onto the watershed lines of a gradient magnitude image and the confidence measure is a function of the cost of fixed-length paths emanating from and extending to each end of a graph arc. The confidence measure is applied to automate the detection of object boundaries and thereby reduces (often greatly) the time and effort required for object boundary definition within a user guided image segmentation environment.

关键词： Object detection Image edge detection Image segmentation Image color analysis Time measurement computer vision Humans Position measurement Detectors Shape control

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Illumination invariant face recognition using thermal infrared imagery

Illumination invariant face recognition using thermal infrar...

引用

conference on computer vision and pattern recognition (cvpr)

作者： D.A. Socolinsky L.B. Wolff J.D. Neuheisel C.K. Eveland Equinox Corporation Baltimore MD USA Equinox Corporation New York NY USA

ISBN: (纸本)0769512720

A key problem for face recognition has been accurate identification under variable illumination conditions. Conventional video cameras sense reflected light so that image grayvalues are a product of both intrinsic skin reflectivity and external incident illumination, thus obfuscating the intrinsic reflectivity of skin. Thermal emission from skin, on the other hand, is an intrinsic measurement that can be isolated from external illumination. We examine the invariance of Long-Wave InfraRed (LWIR) imagery with respect to different illumination conditions from the viewpoint of performance comparisons of two well-known face recognition algorithms applied to LWIR and visible imagery. We develop rigourous data collection protocols that formalize face recognition analysis for computer vision in the thermal IR.

关键词： Lighting Face recognition Infrared imaging Skin Radiometry Calibration Temperature distribution Temperature sensors Layout Cameras

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Minimally supervised acquisition of 3D recognition models from cluttered images

Minimally supervised acquisition of 3D recognition models fr...

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Selinger R.C. Nelson Department of Computer Science University of Rochester Rochester NY USA

ISBN: (纸本)0769512720

Appearance-based object recognition systems rely on training from imagery, which allows the recognition of objects without requiting a 3D geometric model. It has been little explored whether such systems can be trained from imagery that is unlabeled, and whether they can be trained from imagery that is not trivially segmentable. In this paper we present a method for minimally supervised training of a previously developed recognition system from unlabeled and unsegmented imagery. We show that the system can successfully extend an object representation extracted from one black background image to contain object features extracted from unlabeled cluttered images and can use the extended representation to improve recognition performance on a test set.

关键词： Image recognition Object recognition Image segmentation Image databases Shape Surface cleaning computer science Solid modeling Feature extraction System testing

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Generic model abstraction from examples

Generic model abstraction from examples

引用

conference on computer vision and pattern recognition (cvpr)

作者： Y. Keselman S. Dickinson Department of Computer Science Rutgers University New Brunswick NJ USA Department of Computer Science University of Toronto Toronto ONT Canada

ISBN: (纸本)0769512720

The recognition community has long avoided bridging the representational gap between traditional, low-level image features and generic models. Instead, the gap has been artificially eliminated by either bringing the image closer to the models, using simple scenes containing idealized, textureless objects,,or by bringing the models closer to the images, using 3-D CAD model templates or 2-D appearance model templates. In this paper, we attempt to bridge the representational gap for the domain of model acquisition. Specifically, we address the problem of automatically acquiring a generic 2-D view-based class model from a set of images, each containing an exemplar object belonging to that class. We introduce a novel graph-theoretical formulation of the problem, and demonstrate the approach on real imagery.

关键词： Object recognition Image recognition computer science Layout Geometry Electric shock Bridges Solid modeling Councils Prototypes

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