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检索条件"任意字段=2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005"

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Accurate measurement of orientation from stereo using line correspondence

Accurate measurement of orientation from stereo using line c...

引用

conference on computer vision and pattern recognition (cvpr)

作者： L.B. Wolff Computer Science Department Columbia University New York NY USA

The author analyzes a stereo method which determines lines in space from the intersection of projected planar sheets. Object descriptions are built from information about linear features instead of by points. It is shown that there are major advantages to accurately determining the orientation of object lines and surfaces using this stereo method. In the absence of errors (apart from the baseline translation error), the measurement of the orientation of lines and surfaces from this stereo method is translation-invariant in the sense that the orientation measurement is completely independent of knowledge of the baseline. computer simulations of realistic imaging configurations show that, even in the presence of errors from other camera parameters, this stereo method is nearly translation-invariant and can far outperform stereo methods based on the absolute correspondence of points. Another advantage of determining the orientation of lines and surfaces from stereo using intersecting planes is that orientation errors do not grow rapidly as the object distance from the baseline increases.< >

关键词： Position measurement Cameras Robot vision systems Extraterrestrial measurements computer errors Surface fitting computer science Orbital robotics Calibration Particle measurements

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A Generative-Discriminative Hybrid Method for Multi-View Object Detection

A Generative-Discriminative Hybrid Method for Multi-View Obj...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Dong-Qing Zhang Shih-Fu Chang Department of Electrical Engineering Columbia University New York NY USA

We present a novel discriminative-generative hybrid approach in this paper, with emphasis on application in multiview object detection. Our method includes a novel generative model called Random Attributed Relational Graph (RARG) which is able to capture the structural and appearance characteristics of parts extracted from objects. We develop new variational learning methods to compute the approximation of the detection likelihood ratio function. The variaitonal likelihood ratio function can be shown to be a linear combination of the individual generative classifiers defined at nodes and edges of the RARG. Such insight inspires us to replace the generative classifiers at nodes and edges with discriminative classifiers, such as support vector machines, to further improve the detection performance. Our experiments have shown the robustness of the hybrid approach - the combined detection method incorporating the SVM-based discriminative classifiers yields superior detection performances compared to prior works in multiview object detection.

关键词： Hybrid power systems Object detection Iterative algorithms Boosting computer vision Object recognition Government Density functional theory Character generation Learning systems

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Adaptive smoothing: a general tool for early vision

Adaptive smoothing: a general tool for early vision

引用

conference on computer vision and pattern recognition (cvpr)

作者： P. Saint-Marc J.S. Chen G. Medioni Institute for Robotics and Intelligent Systems Departments of Electrical Engineering and Computer Science University of Southern California Los Angeles CA USA

The authors present a method to smooth a signal-whether it is an intensity image, a range image, or a contour-which preserves discontinuities and thus facilitates their detection. This is achieved by repeatedly convolving the signal with a very small averaging filter modulated by a measure of the signal discontinuity at each point. This process is related to the anisotropic diffusion reported by P. Perona and J. Malik (1987) but it has a much simpler formulation and is not subject to instability or divergence. Real examples show how this approach can be applied to the smoothing of various types of signals. The detected features do not move, and thus no tracking is needed. The last property makes it possible to derive a novel scale-space representation of a signal using a small number of scales. Finally, this process is easily implemented on parallel architectures: the running time on a 16 K connection machine is three orders of magnitude faster than on a serial machine.< >

关键词： Smoothing methods Filters Intelligent robots computer vision Intelligent systems Anisotropic magnetoresistance Image edge detection Signal processing Wave functions Laplace equations

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Support vector machines based data detection for holographic data storage systems

Support vector machines based data detection for holographic...

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2005 ieee International conference on Acoustics, Speech, and Signal Processing, ICASSP '05

作者： Ramamoorthy, Lakshmi Keskinoz, Mehmet Kumar, B. V. K. Vijaya Carnegie Mellon University Dept. of Electrical and Computer Engineering Pittsburgh PA 15213 United States Sabanci University Istanbul Turkey

ISBN: (纸本)0780388747

Nonlinear nature of Holographic Data Storage Systems (HDSS) suggests that nonlinear equalization and detection techniques may be beneficial. Complexity involved in nonlinear methods does not often make them practical solutions. Support Vector Machines (SVMs) are recently being studied for pattern recognition applications. We investigated linear SVM detection and observed that the Bit Error Rate (BER) using SVM for data detection on Linear Minimum Mean Squared Error (LMMSE) equalized holographically recorded and retrieved 2-D data pages is about 17% better than the simple threshold detection on unequalized pages. © 2005 ieee.

关键词： Vector quantization

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Studies on silhouette quality and gait recognition

Studies on silhouette quality and gait recognition

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conference on computer vision and pattern recognition (cvpr)

作者： Zongyi Liu L. Malave S. Sarkar Computer Science and Engineering University of South Florida Tampa FL USA

recognition of a person from gait has been a focus in computer vision. It is one biometric source that can be acquired at a distance. At this nascent stage of gait recognition research, the pertinent research questions are those related to understanding the limits of gait recognition and the quantitative study of the various factors effecting gait. However, performances of contemporary algorithms have been confounded by errors in the extracted silhouettes, which has been the low-level representation of choice. In this work, (i) we present to the research community a segmentation "ground truth" research resource consisting of a set of manually specified part-level silhouettes for 70 subjects from the formulated gait challenge database, under different conditions involving change in surface, shoe-type, and time; a total of about 8000 manual silhouettes. (ii) We expound an HMM eigen stance model-based silhouette reconstruction method to correct for common errors in silhouette detection arising from shadows and background subtraction. And (iii) using these "cleaned" silhouettes and the manual silhouettes we show that the effects of various factors such as surface, time, and shoe on gait recognition are not due to poor silhouette quality. In fact, the recognition performance actually drops with the use of "clean " silhouettes because of removal of correlation in the error pixel patterns.

关键词： Surface reconstruction Hidden Markov models computer vision Biometrics Databases Reconstruction algorithms Error correction Surface cleaning Footwear pattern recognition

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Programmable imaging using a digital micromirror array

Programmable imaging using a digital micromirror array

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conference on computer vision and pattern recognition (cvpr)

作者： S.K. Nayar V. Branzoi T.E. Boult Department of Computer Science Columbia University NY USA Department of Computer Science University of Colorado Colorado Springs CO USA

We introduce the notion of a programmable imaging system. Such an imaging system provides a human user or a vision system significant control over the radiometric and geometric characteristics of the system. This flexibility is achieved using a programmable array of micro-mirrors. The orientations of the mirrors of the array can be controlled with high precision over space and time. This enables the system to select and modulate rays from the light field based on the needs of the application at hand. We have implemented a programmable imaging system that uses a digital micro-mirror device (DMD), which is used in digital light processing. Although the mirrors of this device can only be positioned in one of two states, we show that our system can be used to implement a wide variety of imaging functions, including, high dynamic range imaging, feature detection, and object recognition. We conclude with a discussion on how a micro-mirror array can be used to efficiently control field of view without the use of moving parts.

关键词： Micromirrors Mirrors Humans Machine vision Radio control Control systems Radiometry Optical modulation Dynamic range computer vision

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Composite Templates for Cloth Modeling and Sketching

Composite Templates for Cloth Modeling and Sketching

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conference on computer vision and pattern recognition (cvpr)

作者： Hong Chen Zi Jian Xu Zi Qiang Liu Song Chun Zhu Departments of Statistics and Computer Science University of California Los Angeles USA

Cloth modeling and recognition is an important and challenging problem in both vision and graphics tasks, such as dressed human recognition and tracking, human sketch and portrait. In this paper, we present a context sensitive grammar in an And-Or graph representation which will produce a large set of composite graphical templates to account for the wide variabilities of cloth configurations, such as T-shirts, jackets, etc. In a supervised learning phase, we ask an artist to draw sketches on a set of dressed people, and we decompose the sketches into categories of cloth and body components: collars, shoulders, cuff, hands, pants, shoes etc. Each component has a number of distinct subtemplates (sub-graphs). These sub-templates serve as leafnodes in a big And-Or graph where an And-node represents a decomposition of the graph into sub-configurations with Markov relations for context and constraints (soft or hard), and an Or-node is a switch for choosing one out of a set of alternative And-nodes (sub-configurations) - similar to a node in stochastic context free grammar (SCFG). This representation integrates the SCFG for structural variability and the Markov (graphical) model for context. An algorithm which integrates the bottom-up proposals and the topdown information is proposed to infer the composite cloth template from the image.

关键词： Humans Photometry Supervised learning Footwear Switches Statistics computer science computer graphics Stochastic processes Context modeling

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Wire Structure pattern Extraction and Tracking From X-Ray Images of Composite Mechanisms

Wire Structure Pattern Extraction and Tracking From X-Ray Im...

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conference on computer vision and pattern recognition (cvpr)

作者： D. Tschumperle J. Fadili GREYC IMAGE (CNRS UMR 6072) Juin Caen Cedex France

This paper introduces a complete pipeline of image processing methods in order to analyze and track the internal structures of a composite material. As a first step, input Xray images are denoised, enhanced, separated into different morphological components, and geometrically filtered in order to isolate the interesting fiber inside the composite material. This requires the design of specific algorithms preserving very thin image details while being able to remove undesired image regions that may be sometimes large. For this purpose, we use state-of the-art techniques based on recent achievements in diffusion PDE’s and modern harmonic analysis tools. Then, the shapes of the remaining fibered composite are individually analyzed by the use of a tensor-based tracking algorithm. We illustrate how this set of techniques allows the dynamic analysis of the composite structure when submitted to external mechanical loads.

关键词： Wire X-ray imaging Optical fiber devices Image processing Composite materials Image analysis Pipelines Algorithm design and analysis Shape Optical fiber testing

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Recognizing 3D objects from 2D images: an error analysis

Recognizing 3D objects from 2D images: an error analysis

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conference on computer vision and pattern recognition (cvpr)

作者： W.E.L. Grimson D.P. Huttenlocher T.D. Alter AI Laboratory MIT Cambridge MA USA Department of Computer Science Cornell University Ithaca NY USA

Object recognition systems that use a small number of pairings of data and model features to compute the 3D transformation from model to sensor coordinates are considered. The effects of 2D sensor uncertainty on such computations are examined. The uncertainty in transformation parameters is bounded, and the effect of this uncertainty on false positive recognition rates is analyzed.< >

关键词： Image recognition Error analysis Uncertainty Solid modeling Artificial intelligence Laboratories Object recognition Image analysis Integrated circuit modeling computer science

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A Novel Data Association Algorithm for Object Tracking in Clutter with Application to Tennis Video Analysis

A Novel Data Association Algorithm for Object Tracking in Cl...

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conference on computer vision and pattern recognition (cvpr)

作者： Fei Yan A. Kostin W. Christmas J. Kittler Centre for Vision Speech and Signal Processing University of Surrey Guildford Surrey UK

It is well recognised that data association is critically important for object tracking. However, in the presence of successive misdetections, a large number of false candidates and an unknown number of abrupt model switchings that happen unpredictably, the data association problem can be very difficult. We tackle these difficulties by using a layered data association scheme. At the object level, trajectories are "grown" from sets of object candidates that have high probabilities of containing only true positives; by this means the otherwise combinatorial complexity is significantly reduced. Dijkstra’s shortest path algorithm is then used to perform data association at the trajectory level. The algorithm is applied to low-quality tennis video sequences to track a tennis ball. Experiments show that the algorithm is robust to abrupt model switchings, and performs well in heavily cluttered environments.

关键词： Algorithm design and analysis Signal processing algorithms Robustness Iterative algorithms Speech analysis Games Filters Maximum likelihood estimation Polynomials Signal analysis

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