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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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Target detection in foveal ATR systems

Target detection in foveal ATR systems

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Ghosal D.C. McKee Machine Vision Department Amherst Systems Inc. Buffalo NY USA

Automatic target recognition (ATR) applications require simultaneously a wide field of view (FOV) for better detection and situation awareness, high resolution for target recognition and threat assessment, and high frame rate for detecting brief events and disambiguating frame-to-frame correlation. Uniformly sampling the entire FOV at recognition resolution is simply wasteful in ATR scenarios with localized regions of interest (ROIs). Foveal data acquisition with space-variant sampling and context-sensitive sensor articulation is highly optimized for active ATR applications. We propose a multiscale local Zernike filter-based front end target detection technique for a commercially feasible foveal sensor topology with piecewise constant resolution profile. Anisotropic heat diffusion is employed for preprocessing of the foveal data. Expansion template matching is used to derive a detection filter that optimizes the discriminant signal-to-noise ratio (SNR). Results are presented with simulated foveal imagery, derived from real uniform acuity FLIR data.

关键词： Object detection Target recognition Event detection Sampling methods Data acquisition Topology Signal resolution Anisotropic magnetoresistance Matched filters Signal to noise ratio

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Space-time isosurface evolution for temporally coherent 3D reconstruction

Space-time isosurface evolution for temporally coherent 3D r...

引用

conference on computer vision and pattern recognition (cvpr)

作者： B. Goldluecke M. Magnor Graphics-Optics-Vision Max Planck Institut für Informatik Saarbruecken Germany

We model the dynamic geometry of a time-varying scene as a 3D isosurface in space-time. The intersection of the isosurface with planes of constant time yields the geometry at a single time instant. An optimal fit of our model to multiple video sequences is defined as the minimum of an energy functional. This functional is given by an integral over the entire hypersurface, which is designed to optimize photo-consistency. A PDE-based evolution derived from the Euler-Lagrange equation maximizes consistency with all of the given video data simultaneously. The result is a 3D model of the scene which varies smoothly over time. The geometry reconstructed by this scheme is significantly better than results obtained by space-carving approaches that do not enforce temporal coherence.

关键词： Isosurfaces Layout Image reconstruction Geometry Surface reconstruction Solid modeling Level set Rendering (computer graphics) Video sequences Equations

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Using the inner-distance for classification of articulated shapes

Using the inner-distance for classification of articulated s...

引用

conference on computer vision and pattern recognition (cvpr)

作者： H. Ling D.W. Jacobs Computer Science Department University of Maryland College Park USA

We propose using the inner-distance between landmark points to build shape descriptors. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that the inner-distance is articulation insensitive and more effective at capturing complex shapes with part structures than Euclidean distance. To demonstrate this idea, it is used to build a new shape descriptor based on shape contexts. After that, we design a dynamic programming based method for shape matching and comparison. We have tested our approach on a variety of shape databases including an articulated shape dataset, MPEG7 CE-Shape-1, Kimia silhouettes, a Swedish leaf database and a human motion silhouette dataset. In all the experiments, our method demonstrates effective performance compared with other algorithms.

关键词： Euclidean distance Dynamic programming Databases Shape measurement Testing Jacobian matrices computer science Educational institutions MPEG 7 Standard Humans

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Extracting symmetry features from color images

Extracting symmetry features from color images

引用

conference on computer vision and pattern recognition (cvpr)

作者： Bea Thai G. Healey Computer Vision Laboratory Electrical and Computer Engineering University of California Irvine CA USA

We develop methods to extract semantically meaningful symmetries from color images. These symmetries are defined within and between color bands using complex moments computed from the output of a bank of orientation and scale selective filters. From this representation, we derive a set of features which are invariant to rotation, scale, and illumination conditions. Experimental results are provided to show the performance of this set of features for classification and image database partitioning.

关键词： Feature extraction Color Frequency domain analysis Lighting Image databases computer vision Laboratories Filters Information retrieval Image retrieval

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Radiometric alignment of image sequences

Radiometric alignment of image sequences

引用

conference on computer vision and pattern recognition (cvpr)

作者： Seon Joo Kim M. Pollefeys Department of Computer Science North Carolina State University Chapel Hill NC USA

Color values in an image are related to image irradiance by a nonlinear function called radiometric response function. Since this function depends on the aperture and the shutter speed, image intensity of a same object may vary during the acquisition of an image sequence due to auto exposure feature of the camera. While this is desirable to make optimal use of the limited dynamic range of most cameras, this causes problems for a number of applications in computer vision. In this paper we propose a method for estimating the radiometric response function and apply it to radiometrically align images so that the color values are consistent for all images of a sequence. Our approach computes the response function, exposure and white balance changes between images (up to some ambiguity) for a moving camera without any prior knowledge about exposures. We show the performance of our algorithm by estimating the response function from synthetic images and also from real world data, using it to radiometrically align the images.

关键词： Radiometry Image sequences Layout Dynamic range computer vision Brightness Shape measurement Application software Digital cameras Iterative algorithms

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Real-time tracking with multiple cues by set theoretic random search

Real-time tracking with multiple cues by set theoretic rando...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Cheng Chang R. Ansari Microsoft Corporation USA ECE Department University of Illinois Chicago IL USA

Conventional treatment of visual tracking has been to optimize an objective function in a probabilistic framework. In this formulation, efficient algorithms employing simple prior distributions are usually insufficient to handle clutters (e.g., Kalman filter). On the other hand, distributions that are complex enough to incorporate all a priori knowledge can make the problem computationally intractable (e.g., particle filters (PF)). This paper proposes a new formulation of visual tracking where every piece of information, be it from a priori knowledge or observed data, is represented by a set in the solution space and the intersection of these sets, the feasibility set, represents all acceptable solutions. Based on this formulation, we propose an algorithm whose objective is to find a solution in the feasibility set. We show that this set theoretic tracking algorithm performs effective face tracking and is computationally more efficient than standard PF-based tracking.

关键词： Target tracking Particle filters Bayesian methods Stochastic processes computer vision Robustness Shape measurement Particle tracking Optimization methods Distributed computing

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Improved Likelihood Function in Particle-based IR Eye Tracking

Improved Likelihood Function in Particle-based IR Eye Tracki...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： D. Witzner Hansen R. Satria J. Sorensen R. Hammoud Dept. of Innovation IT University Copenhagen Denmark Delphi Electronics and Safety Kokomo Indiana USA Dept. of Innovation IT University Copenhagen

In this paper we propose a log likelihood-ratio function of foreground and background models used in a particle filter to track the eye region in dark-bright pupil image sequences. This model fuses information from both dark and bright pupil images and their difference image into one model. Our enhanced tracker overcomes the issues of prior selection of static thresholds during the detection of feature observations in the bright-dark difference images. The auto-initialization process is performed using cascaded classifier trained using adaboost and adapted to IR eye images. Experiments show good performance in challenging sequences with test subjects showing large head movements and under significant light conditions.

关键词： Particle tracking Lighting Face detection Eyes Layout Light sources computer vision Head Humans Robustness

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Extended-Regular Sequence for Automated Analysis of Microarray Images

Extended-Regular Sequence for Automated Analysis of Microarr...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Hee-Jeong Jin Bong-Kyung Chun Hwan-Gue Cho Department of Computer Engineering Pusan National University busan South Korea

A variety of high throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy for can be applied in the analysis of data sets of thousands of genes during cellular differentiation and response.

关键词： Image analysis Image sequence analysis Throughput Wavelet analysis pattern analysis Wavelet transforms Delay effects Propagation delay Microorganisms Data analysis

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Video-based Human Action *** with Ambiguous Correspondences

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Zhou Feng Tat-Jen Cham School of Computer Engineering Nanyang Technological University Singapore

This paper describes a combined tracking-classification framework for the unsupervised classification of human action. While most existing approaches assume that featurewise correspondences on people are either available or not at all, this method explicitly formalizes how the probability of correspondences can be used in computation when the correspondences are ambiguous. It is also able to exploit in a probabilistic manner any foreground-background preprocessed segmentation, even if the segmentation is of low confidence. A principled analysis of the problem leads to a novel probabilistic action representation called the correspondence-ambiguous feature histogram array (CAFHA) that is robust to variations across similar actions. Our results show that the new framework outperforms the recent Zelnik-Manor and Irani method [19] for unsupervised event classi?cation. Additionally, the framework is extended to quasi real-time action inference, achieving good recognition accuracy despite changes in person identity and variations in the actions.

关键词： Humans Unsupervised learning Biological system modeling State estimation Video sequences Kinematics Motion analysis Feature extraction pattern recognition computer errors

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A fast multigrid implicit algorithm for the evolution of geodesic active contours

A fast multigrid implicit algorithm for the evolution of geo...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Papandreou P. Maragos School of Electrical and Computer Engin National and Technical University of Athens Athens Greece

Active contour models are among the most popular PDE-based tools in computer vision. In this paper we present a new algorithm for the fast evolution of geodesic active contours and compare it with other established numerical schemes. The new algorithm employs a full time-implicit and unconditionally stable numerical scheme and applies multigrid methods for the efficient solution of the occurring sparse linear system. When we utilize very big time-steps for the numerical evolution of the front, the proposed scheme has increased accuracy and better rotational invariance properties compared with the alternative AOS scheme. This allows for the rapid evolution and convergence of the contour to its final configuration after only very few iterations. Standard pyramidal and/or narrowband techniques can be easily integrated into our algorithm and further accelerate the curve evolution. Experimental results in object boundary detection demonstrate the power of the method.

关键词： Active contours computer vision Object detection Level set Geophysics computing Narrowband Solid modeling Stability Multigrid methods Linear systems

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