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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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MUSE: robust surface fitting using unbiased scale estimates

MUSE: robust surface fitting using unbiased scale estimates

引用

conference on computer vision and pattern recognition (cvpr)

作者： J.V. Miller C.V. Stewart Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA Department of Computer Science Rensselaer Polytechnic Institute Troy NY USA

Despite many successful applications of robust statistics, they have yet to be completely adapted to many computer vision problems. Range reconstruction, particularly in unstructured environments, requires a robust estimator that not only tolerates a large outlier percentage but also tolerates several discontinuities, extracting multiple surfaces in an image region. Observing that random outliers and/or points from across discontinuities increase a hypothesized fit's scale estimate (standard deviation of the noise), our new operator; called MUSE (Minimum Unbiased Scale Estimator), evaluates a hypothesized fit over potential inlier sets via an objective function of unbiased scale estimates. MUSE extracts the single best fit from the data by minimizing its objective function over a set of hypothesized fits and can sequentially extract multiple surfaces from an image region. We show MUSE to be effective on synthetic data modelling small scale discontinuities and in preliminary experiments on complicated range data.

关键词： Surface fitting Robustness Data mining Surface reconstruction Application software computer vision World Wide Web Economic indicators Image reconstruction Bridges

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Visual landmarks detection and recognition for mobile robot navigation

Visual landmarks detection and recognition for mobile robot ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J.B. Hayet F. Lerasle M. Devy LAAS CNRS Toulouse France

This article describes visual functions dedicated to the extraction and recognition of planar quadrangles detected from a single camera. Extraction is based on a relaxation scheme with constraints between image segments, while the characterization we propose allows recognition to be achieved from different view-points and viewing conditions. We defined and evaluated several metrics on this representation space - a correlation-based one and another one based on sets of interest points.

关键词： Mobile robots Navigation Robot vision systems Cameras Character recognition Image recognition Robustness Matched filters Image segmentation Extraterrestrial measurements

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Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs

Cosegmentation of Image Pairs by Histogram Matching - Incorp...

引用

conference on computer vision and pattern recognition (cvpr)

作者： C. Rother T. Minka A. Blake V. Kolmogorov Microsoft Research Cambridge UK University College London UK

We introduce the term cosegmentation which denotes the task of segmenting simultaneously the common parts of an image pair. A generative model for cosegmentation is presented. Inference in the model leads to minimizing an energy with an MRF term encoding spatial coherency and a global constraint which attempts to match the appearance histograms of the common parts. This energy has not been proposed previously and its optimization is challenging and NP-hard. For this problem a novel optimization scheme which we call trust region graph cuts is presented. We demonstrate that this framework has the potential to improve a wide range of research: Object driven image retrieval, video tracking and segmentation, and interactive image editing. The power of the framework lies in its generality, the common part can be a rigid/non-rigid object (or scene), observed from different viewpoints or even similar objects of the same class.

关键词： Histograms Image segmentation Layout computer vision Error correction Educational institutions Encoding Spatial coherence Image retrieval Information resources

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Accurate Face Alignment using Shape Constrained Markov Network

Accurate Face Alignment using Shape Constrained Markov Netwo...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Lin Liang Fang Wen Ying-Qing Xu Xiaoou Tang Heung-Yeung Shum Visual Computing Group Microsoft Research Asia Beijing China

In this paper, we present a shape constrained Markov network for accurate face alignment. The global face shape is defined as a set of weighted shape samples which are integrated into the Markov network optimization. These weighted samples provide structural constraints to make the Markov network more robust to local image noise. We propose a hierarchical Condensation algorithm to draw the shape samples efficiently. Specifically, a proposal density incorporating the local face shape is designed to generate more samples close to the image features for accurate alignment, based on a local Markov network search. A constrained regularization algorithm is also developed to weigh favorably those points that are already accurately aligned. Extensive experiments demonstrate the accuracy and effectiveness of our proposed approach.

关键词： Markov random fields Facial animation Deformable models Inference algorithms Noise shaping computer vision Face detection Parameter estimation Active shape model Principal component analysis

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Contour matching using local affine transformations

Contour matching using local affine transformations

引用

conference on computer vision and pattern recognition (cvpr)

作者： I.A. Bachelder S. Ullman Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

A noniterative scheme for determining contour matches using locally affine transformations is proposed. The method assumes that contours are approximated by the orthographic projection of planar patches within oriented neighborhoods of varying sizes. For degenerate cases, a minimal matching solution is chosen closest to the minimal pure translation. Performance on noisy synthetic and natural contour imagery is reported.< >

关键词： Least squares approximation Optical sensors Image motion analysis Stability Computed tomography Artificial intelligence Laboratories Object recognition Motion measurement Apertures

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Detecting unusual activity in video

Detecting unusual activity in video

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conference on computer vision and pattern recognition (cvpr)

作者： Hua Zhong Jianbo Shi M. Visontai Computer Science Department Carnegie Mellon University Pittsburgh PA USA Computer and Information Science University of Pennsylvania Philadelphia PA USA

We present an unsupervised technique for detecting unusual activity in a large video set using many simple features. No complex activity models and no supervised feature selections are used. We divide the video into equal length segments and classify the extracted features into prototypes, from which a prototype-segment co-occurrence matrix is computed. Motivated by a similar problem in document-keyword analysis, we seek a correspondence relationship between prototypes and video segments which satisfies the transitive closure constraint. We show that an important sub-family of correspondence functions can be reduced to co-embedding prototypes and segments to N-D Euclidean space. We prove that an efficient, globally optimal algorithm exists for the co-embedding problem. Experiments on various real-life videos have validated our approach.

关键词： Event detection Feature extraction Prototypes Hidden Markov models Image segmentation Object detection computer science Information science Layout Surveillance

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On the derivation of geometric constraints in stereo

On the derivation of geometric constraints in stereo

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conference on computer vision and pattern recognition (cvpr)

作者： C.V. Stewart Department of Computer Science and New York State Center for Advanced Technology in Automation and Robotics Rensselaer Polytechnic Institute Troy NY USA

Probability density functions (PDFs) are derived for many of the geometric measurements upon which stereo matching techniques are based, including orientation differences between matching line segments or curves, the gradient of disparity, the directional derivative of disparity, and disparity differences between matches. The PDFs resulting from the transformations are used to critically examine many existing stereo techniques. Several techniques based on these PDFs are proposed.< >

关键词： Layout Cameras Geometry Robotics and automation Probability density function Image segmentation Solid modeling Jacobian matrices Measurement uncertainty computer science

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Using stereomotion to track binocular targets

Using stereomotion to track binocular targets

引用

conference on computer vision and pattern recognition (cvpr)

作者： M.R.M. Jenkin Department of Computer Science York University Downsview ONT Canada

An algorithm is presented for the smooth tracking of a target in three-dimensional space by a binocular head which is capable of vergence, version, and tilt eye movements. This algorithm utilizes stereomotion channels to obtain a measurement of the three-dimensional velocity of the target, and then uses this velocity within a control loop to keep the target center at the fixation point of the binocular head. Although stereomotion alone is insufficient to accurately drive binocular eye movements, relative stereomotion is a useful measurement and could be easily integrated into a positional error driven tracking system.< >

关键词： Target tracking Cameras Head Position measurement Hardware Visual system Eyes computer science computer vision Velocity measurement

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An analysis of the probability of disparity changes in stereo matching and a new algorithm based on the analysis

An analysis of the probability of disparity changes in stere...

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conference on computer vision and pattern recognition (cvpr)

作者： C.V. Stewart Department of Computer Science Rensselaer Polytechnic Institute Troy NY USA

The main contributions of this research are: (1) the derivation of the probability density function (pdf) of disparity changes in stereo matching based on the pdf of depth changes in the world and on the parameters of the stereo image formation process, (2) the definition of a match support equation based on the derived pdf, and (3) the incorporation of the support equation into a relaxation matching algorithm. The derived pdf and support equation are applicable to many existing stereo algorithms.< >

关键词： Algorithm design and analysis Equations Image analysis Image converters computer science Probability density function Image sampling Cameras Lenses Length measurement

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Video Completion by Motion Field Transfer

Video Completion by Motion Field Transfer

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conference on computer vision and pattern recognition (cvpr)

作者： T. Shiratori Y. Matsushita Xiaoou Tang Sing Bing Kang University of Tokyo Tokyo Japan Microsoft Research Asia Beijing China Microsoft Research Limited WA USA

Existing methods for video completion typically rely on periodic color transitions, layer extraction, or temporally local motion. However, periodicity may be imperceptible or absent, layer extraction is difficult, and temporally local motion cannot handle large holes. This paper presents a new approach for video completion using motion field transfer to avoid such problems. Unlike prior methods, we fill in missing video parts by sampling spatio-temporal patches of local motion instead of directly sampling color. Once the local motion field has been computed within the missing parts of the video, color can then be propagated to produce a seamless hole-free video. We have validated our method on many videos spanning a variety of scenes. We can also use the same approach to perform frame interpolation using motion fields from different videos.

关键词： Sampling methods Asia Layout Filling Image restoration Videoconference computer vision Interpolation Internet Streaming media

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