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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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The alignment of objects with smooth surfaces: error analysis of the curvature method

The alignment of objects with smooth surfaces: error analysi...

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Basri M. I. T. A. I. Laboratory Cambridge MA USA

The recognition of objects with smooth bounding surfaces from their contour images is addressed. In particular, the curvature method is applied to ellipsoidal objects and the error for different rotations of the objects is computed analytically. It is seen that the error depends on the exact shape of the ellipsoid (namely, the relative lengths of its axes), and it increases as the ellipsoid becomes elongated in the Z-direction. It is shown that the errors are usually small, and that, in general, a small number of models is required to predict the appearance of an ellipsoid from all possible views.< >

关键词： Error analysis Ellipsoids Shape Laboratories Predictive models Image recognition Object recognition Neuroscience Artificial intelligence Contracts

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A Rao-Blackwellized particle filter for EigenTracking

A Rao-Blackwellized particle filter for EigenTracking

引用

conference on computer vision and pattern recognition (cvpr)

作者： Zia Khan T. Balch F. Dellaert College of Computing Georgia Institute of Technology USA

Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully applied in tracking. For noisy targets, optimization-based algorithms (including EigenTracking) often fail catastrophically after losing track. Particle filters have recently emerged as a robust method for tracking in the presence of multi-modal distributions. To use subspace representations in a particle filter, the number of samples increases exponentially as the state vector includes the subspace coefficients. We introduce an efficient method for using subspace representations in a particle filter by applying Rao-Blackwellization to integrate out the subspace coefficients in the state vector. Fewer samples are needed since part of the posterior over the state vector is analytically calculated. We use probabilistic principal component analysis to obtain analytically tractable integrals. We show experimental results in a scenario in which we track a target in clutter.

关键词： Particle filters Target tracking computer vision Principal component analysis Shape Vectors Particle measurements Robustness Particle tracking State estimation

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Calibration of a foveated wide-angle lens on an active vision head

Calibration of a foveated wide-angle lens on an active visio...

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conference on computer vision and pattern recognition (cvpr)

作者： L. Berthouze S. Rougeaux F. Chavand Y. Kuniyoshi Autonomous Systems Section Electro Technical Laboratory Tsukuba Ibaraki Japan Equipe Systemes Complexes Centre dE28099Etudes Mecaniques dIE28099le de France Evry France

Inspired by the properties of the human visual system, a new active vision system called ESCHeR (Etl Stereo Compact Head For Robot vision) has been recently implemented with foveated wide angle lenses. The lenses exhibit a wide field of view along with a space-varying resolution for facilitating both detection and close observation. However, to handle such optical properties and achieve basic eye movement functions, new calibration methods are needed. Therefore, two novel and online techniques are presented that in one case perform a global identification of the optical process through artificial neural techniques and in the other case compute the physical parameters by using environmental feature-tracking and controlled rotations of the cameras. Self-alignment of the cameras is also achieved using a similar technique.

关键词： Calibration Lenses Cameras Humans Visual system Machine vision Orbital robotics Robot vision systems Optical computing Physics computing

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Accurate measurement of orientation from stereo using line correspondence

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

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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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Adaptive smoothing: a general tool for early vision

Adaptive smoothing: a general tool for early vision

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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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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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Appearance modeling for tracking in multiple non-overlapping cameras

Appearance modeling for tracking in multiple non-overlapping...

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conference on computer vision and pattern recognition (cvpr)

作者： O. Javed K. Shafique M. Shah Computer Vision Laboratory University of Central Florida Orlando FL USA

When viewed from a system of multiple cameras with non-overlapping fields of view, the appearance of an object in one camera view is usually very different from its appearance in another camera view due to the differences in illumination, pose and camera parameters. In order to handle the change in observed colors of an object as it moves from one camera to another, we show that all brightness transfer functions from a given camera to another camera lie in a low dimensional subspace and demonstrate that this subspace can be used to compute appearance similarity. In the proposed approach, the system learns the subspace of inter-camera brightness transfer functions in a training phase during which object correspondences are assumed to be known. Once the training is complete, correspondences are assigned using the maximum a posteriori (MAP) estimation framework using both location and appearance cues. We evaluate the proposed method under several real world scenarios obtaining encouraging results.

关键词： Cameras Brightness computer vision Transfer functions Lighting Layout Material properties Training data Trajectory Surveillance

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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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Segmentation and grouping of object boundaries using energy minimization

Segmentation and grouping of object boundaries using energy ...

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conference on computer vision and pattern recognition (cvpr)

作者： D.A. Trytten M. Tuceryan Department of Computer Science Michigan State University East Lansing MI USA

An algorithm is described which performs curvilinear grouping of image edge elements for detecting object boundaries. The method works by generating hypotheses and selecting the best one. A neighborhood definition based on Delaunay graph is used to keep the number of generated hypotheses small. An energy minimizing curve is fit to the generated hypotheses to evaluate the grouping and locate discontinuities.< >

关键词： Image edge detection Object detection Image segmentation Minimization methods computer science Detection algorithms Image reconstruction Humans Data preprocessing Detectors

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