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International Conference on Pattern Recognition

作者： A.M. Bruckstein E. Rivlin I. Weiss Department of Computer Science Israel Institute of Technology-Technion Haifa Israel Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD USA

In this paper we discuss a new approach to invariant signatures for recognizing curves under viewing distortions and partial occlusion. The approach is intended to overcome the ill-posed problem of finding derivatives, on which local invariants usually depend. The basic idea is to use invariant finite differences, with a scale parameter that determines the size of the differencing interval. The scale parameter is allowed to vary so that a "scale space"-like invariant representation of the curve, with larger difference intervals corresponding to larger coarser scales, can be obtained. In this new representation, each traditional local invariant is replaced by a scale-dependent range of invariants. Thus, instead of invariant signature curves we obtain invariant signature surfaces in a 3D invariant "scale space".

关键词： Shape computer vision computer science Finite difference methods Object recognition Laboratories Automation Educational institutions Polynomials Gaussian processes

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TACTICAL ROUTE PLANNING: NEW ALGORITHMS FOR DECOMPOSING THE MAP

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International Journal on Artificial Intelligence Tools 1996年第1N02期5卷 199-218页

作者： J.R. BENTON S.S. IYENGAR W. DENG N. BRENER V.S. SUBRAHMANIAN Modeling and Simulation Division U.S. Army Topographic Engineering Center 7701 Telegraph Road Alexandria VA 22315–3864 USA Department of Computer Science & Robotics Research Laboratory Louisiana State University Baton Rouge LA 70803–4020 USA Department of Computer Science & Institute for Advanced Computer Studies University of Maryland College Park Maryland 20742 USA

This paper defines a new approach and investigates a fundamental problem in route planners. This capability is important for robotic vehicles(Martian Rovers, etc.) and for planning off-road military maneuvers. The emphasis throughout this paper will be on the design and analysis and hieiaichical implementation of our route planner. This work was motivated by anticipation of the need to search a grid of a trillion points for optimum routes. This cannot be done simply by scaling upward from the algorithms used to search a grid of 10,000 points. Algorithms sufficient for the small grid are totally inadequate for the large grid. Soon, the challenge will be to compute off-road routes more than 100 km long and with a one or two-meter grid. Previous efforts are reviewed and the data structures, decomposition methods and search algorithms are analyzed and limitations are discussed. A detailed discussion of a hieraichical implementation is provided and the experimental results are analyzed.

关键词： Route planning heirarchical planning A* algorithm robotic vehicles

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Cardboard people: a parameterized model of articulated image motion

Cardboard people: a parameterized model of articulated image...

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International Conference on Automatic Face and Gesture Recognition

作者： S.X. Ju M.J. Black Y. Yacoob Department of Computer Science University of Toronto Toronto ONT Canada Xerox Palo Alto Research Center Palo Alto CA USA Computer Vision Laboratory University of Maryland College Park MD USA

We extend the work of Black and Yacoob (1995) on the tracking and recognition of human facial expressions using parametrized models of optical flow to deal with the articulated motion of human limbs. We define a "card-board person model" in which a person's limbs are represented by a set of connected planar patches. The parametrized image motion of these patches in constrained to enforce articulated motion and is solved for directly using a robust estimation technique. The recovered motion parameters provide a rich and concise description of the activity that can be used for recognition. We propose a method for performing view-based recognition of human activities from the optical flow parameters that extends previous methods to cope with the cyclical nature of human motion. We illustrate the method with examples of tracking human legs of long image sequences.

关键词： Biological system modeling Tracking Brightness Motion estimation Humans Equations Image recognition Image motion analysis Active contours Shape

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Fingerprint enhancement

Fingerprint enhancement

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IEEE Workshop on Applications of computer vision (WACV)

作者： Lin Hong A. Jian S. Pankanti R. Bolle Department of Computer Science Michigan State University East Lansing MI USA Michigan State University East Lansing MI US Exploratory Computer Vision Group IBM Thomas J. Watson Research Center Yorktown Heights NY USA

Fingerprint images vary in quality. In order to ensure that the performance of an automatic fingerprint identification system (AFIS) will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement module in the AFIS system. We introduce a new fingerprint enhancement algorithm which decomposes the input fingerprint image into a set of filtered images. From the filtered images, the orientation field is estimated and a quality mask which distinguishes the recoverable and unrecoverable corrupted regions in the input image is generated. The input fingerprint image is adaptively enhanced in the recoverable regions. The performance of our algorithm has been evaluated on an online fingerprint verification system using the MSU fingerprint database containing over 600 fingerprint images. Experimental results show that our enhancement algorithm improves the performance of the online fingerprint verification system and makes it more robust with respect to the quality of input fingerprint images.

关键词： Fingerprint recognition Image matching Robustness computer science Image databases Epidermis computer vision Bifurcation

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A 3D local energy surface detector for confocal microscope imalges 3

A 3D local energy surface detector for confocal microscope i...

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3rd Australian and New Zealand Conference on Intelligent Information Systems, ANZIIS 1995

作者： Pudney, Chris Kovesi, Peter Robbins, Ben Biomedical Confocal Microscopy Research Centre Department of Pharmacology United States Robotics and Vision Research Group Department of Computer Science University of Western Australia NedlandsWA6907 Australia

ISBN: (纸本)0864224303

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature profiles: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters. The filters are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency-space and multiplied by the image's Fourier transform. Results are presented for real confocal images and synthetic 3D image volumes. © 1995 IEEE. All rights reserved.

关键词： Microscopes

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Feature detection using oriented local energy for 3D confocal microscope images 3rd

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3rd International computer science Conference, ICSC 1995

作者： Pudney, Chris Kovesi, Peter Robbins, Ben Biomedical Confocal Microscopy Research Centre Department of Pharmacology The University of Western Australia NedlandsWA6907 Australia Robotics and Vision Research Group Department of Computer Science The University of Western Australia NedlandsWA6907 Australia

ISBN: (纸本)9783540606970

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature types: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters that are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency-space and multiplied by the image's Fourier transform. Results are presented for real confocal images and a synthetic 3D image volume. These results are compared with those from a 3D implementation of the Sobel edge detecto. © Springer-Verlag Berlin Heidelberg 1995.

关键词： Feature extraction

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Global rigidity constraints in image displacement fields

Global rigidity constraints in image displacement fields

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International Conference on computer vision (ICCV)

作者： C. Fermuller Y. Aloimonos Computer Vision Laboratory Center for Automation Research Department of Computer Science and Institute for Advanced Computer Studies University of Maryland MD USA

Image displacement fields-optical flow fields, stereo disparity fields, normal flow fields-due to rigid motion possess a global geometric structure which is independent of the scene in view. Motion vectors of certain lengths and directions are constrained to lie on the imaging surface at particular loci whose location and form depends solely on the 3D motion parameters. If optical flow fields or stereo disparity fields are considered, then equal vectors are shown to lie on conic sections. Similarly, for normal motion fields, equal vectors lie within regions whose boundaries also constitute conics. By studying various properties of these curves and regions and their relationships, a characterization of the structure of rigid motion fields is given. The goal of this paper is to introduce a concept underlying the global structure of image displacement fields. This concept gives rise to various constraints that could form the basis of algorithms for the recovery of visual information from multiple views.< >

关键词： Motion measurement Layout Stereo vision Image motion analysis computer vision Motion estimation Fluid flow measurement Laboratories Automation computer science

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Detection of independently moving objects in passive video

Detection of independently moving objects in passive video

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IEEE Symposium on Intelligent Vehicle

作者： C. Morimoto D. DeMenthon L. Davis R. Chellappa R. Nelson Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD USA Department of Computer Science University of Rochester Rochester NY USA

We present two different approaches for the identification of independently moving objects (IMOs) and demonstrate their application to outdoor imagery taken from a moving autonomous vehicle. Both approaches involve image stabilization followed by an analysis of the stabilized image sequence. The stabilization reduces the effects of the movement of the autonomous vehicle, facilitating the detection of the IMOs. In the first approach, IMOs are detected based on a filtering approach that integrates the results of velocity tuned filters over several frames. In the second approach IMOs are identified by constraints on allowable values of the optic flow field after stabilization.

关键词： Object detection Optical filters Remotely operated vehicles Mobile robots Vehicle detection Image analysis Image sequence analysis Image sequences Filtering Image motion analysis

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Recognizing functionality

Recognizing functionality

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International Symposium on computer vision (ISCV)

作者： Z. Duric J. Fayman E. Rivlin Computer Vision Laboratory Center For Automation Research University of Maryland College Park MD USA Department of Computer Science Israel Institute of Technology-Technion Haifa Israel

We look into a new area of function recognition: determining the function of an object from its motion. Given a sequence of images of a known object performing some function, we attempt to determine what that function is. We show that the motion of an object, when combined with information about the object and its normal uses, provides us with strong constraints on possible functions that the object might be performing.

关键词： Motion analysis Acceleration Image sequence analysis computer vision Laboratories Automation Educational institutions Human robot interaction Usability Shape

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Randomized query processing in robot path planning 95

Randomized query processing in robot path planning

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Proceedings of the twenty-seventh annual ACM symposium on Theory of computing

作者： Lydia E. Kavraki Jean-Claude Latombe Rajeev Motwani Prabhakar Raghavan Robotics Laboratory Department of Computer Science Stanford University Stanford CA Department of Computer Science Stanford University Stanford CA IBM Research Division T.J. Watson Research Center Yorktown Heights NY

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