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Shape-time photography

Shape-time photography

引用

conference on computer vision and pattern recognition (cvpr)

作者： W.T. Freeman Hao Zhang EECS Department Massachusetts Institute of Technology Cambridge MA USA EECS Department University of California Berkeley Berkeley CA USA

We introduce a new method to describe shape relationships over time in a photograph. We acquire both range and image information in a sequence of frames using a stationary stereo camera. From the pictures taken, we compute a composite image consisting of the pixels from the surfaces closest to the camera over all the time frames. Through occlusion cues, this composite reveals 3-D relationships between the shapes at different times. We call the composite a shape-time photograph. Small errors in stereo depth measurements can create artifacts in the shape-time images. We correct most of these using a Markov network to estimate the most probable front-surface pixel, taking into account (a) the stereo depth measurements and their uncertainties, and (b) spatial continuity assumptions for the time-frame assignments of the front-surface pixels.

关键词： Photography Pixel Shape measurement Cameras Stereo vision computer vision Markov random fields Measurement uncertainty Time measurement Rendering (computer graphics)

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Recognizing objects in adversarial clutter: breaking a visual CAPTCHA

Recognizing objects in adversarial clutter: breaking a visua...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Mori J. Malik Computer Science Division University of California Berkeley Berkeley CA USA

In this paper we explore object recognition in clutter. We test our object recognition techniques on Gimpy and EZ-Gimpy, examples of visual CAPTCHAs. A CAPTCHA ("Completely Automated Public Turing test to Tell computers and Humans Apart") is a program that can generate and grade tests that most humans can pass, yet current computer programs can't pass. EZ-Gimpy, currently used by Yahoo, and Gimpy are CAPTCHAs based on word recognition in the presence of clutter. These CAPTCHAs provide excellent test sets since the clutter they contain is adversarial; it is designed to confuse computer programs. We have developed efficient methods based on shape context matching that can identify the word in an EZ-Gimpy image with a success rate of 92%, and the requisite 3 words in a Gimpy image 33% of the time. The problem of identifying words in such severe clutter provides valuable insight into the more general problem of object recognition in scenes. The methods that we present are instances of a framework designed to tackle this general problem.

关键词： Humans Artificial intelligence Object recognition Automatic testing computer science Shape Layout Internet Postal services Dictionaries

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Constrained subspace modeling

Constrained subspace modeling

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Vermaak P. Perez Engineering Department University of Cambridge Cambridge UK Microsoft Research Limited Cambridge UK

When performing subspace modeling of data using principal component analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the problem being investigated. This need arises due to the data often being approximately isotropic along the lesser principal components, making the choice of directions for these components more-or-less arbitrary. Furthermore, constraining may be imperative to ensure viable solutions in problems where the dimensionality of the data space is of the same order as the number of data points available. This paper adopts a Bayesian approach and augments the likelihood implied by probabilistic principal component analysis (PPCA) (Tipping and Bishop, 1999) with a prior designed to achieve the constraining effect. The subspace parameters are computed efficiently using the EM algorithm. The constrained modeling approach is illustrated on two pertinent problems, one from speech analysis, and one from computer vision.

关键词： Subspace constraints Principal component analysis Bayesian methods computer vision Data engineering Context modeling Speech analysis Data visualization Gaussian noise Gaussian distribution

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Estimating 3D hand pose from a cluttered image

Estimating 3D hand pose from a cluttered image

引用

conference on computer vision and pattern recognition (cvpr)

作者： V. Athitsos S. Sclaroff Computer Science Department Boston University Boston MA USA

A method is proposed that can generate a ranked list of plausible three-dimensional hand configurations that best match an input image. Hand pose estimation is formulated as an image database indexing problem, where the closest matches for an input hand image are retrieved from a large database of synthetic hand images. In contrast to previous approaches, the system can function in the presence of clutter, thanks to two novel clutter-tolerant indexing methods. First, a computationally efficient approximation of the image-to-model chamfer distance is obtained by embedding binary edge images into a high-dimensional Euclidean space. Second, a general-purpose, probabilistic line matching method identifies those line segment correspondences between model and input images that are the least likely to have occurred by chance. The performance of this clutter tolerant approach is demonstrated in quantitative experiments with hundreds of real hand images.

关键词： Image databases Indexing Impedance matching Image retrieval Image segmentation Information retrieval computer vision computer science Embedded computing Humans

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Range image segmentation by surface extraction using an improved robust estimator

Range image segmentation by surface extraction using an impr...

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conference on computer vision and pattern recognition (cvpr)

作者： P.F.U. Gotardo O.R.P. Bellon L. Silva Departamento de Informatica Universidade Federal do Parana Brazil Centro Federal de Educacao Tecnologica do Parana CPGEI Brazil

The paper presents a novel range image segmentation algorithm based on planar surface extraction. The algorithm was applied to common range image databases and was favorably compared against seven other segmentation algorithms using a popular evaluation framework. The experimental results show that, as compared to the other methods, our algorithm presents a good performance in preserving small regions and edge locations when processing noisy images. Our main contribution is an improved robust estimator, derived from the RANSAC and MSAC estimators, whose optimization process is accelerated by a genetic algorithm with a new set of parameters and operations designed to avoid premature convergence.

关键词： Image segmentation Robustness Surface fitting computer vision Object recognition Layout Solid modeling Parameter estimation Genetic algorithms Convergence

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Low-dimensional representations of shaded surfaces under varying illumination

Low-dimensional representations of shaded surfaces under var...

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conference on computer vision and pattern recognition (cvpr)

作者： P. Nillius J.-O. Eklundh Computational Vision & Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology Stockholm Sweden

The aim of this paper is to find the best representation for the appearance of surfaces with Lambertian reflectance under varying illumination. Previous work using principal component analysis (PCA) found the best sub-space to represent all images of an object under a varying point light source. We extend this to images from any illumination distribution. Specifically we calculate the bases for all configurations of a point plus ambient light source and two point light sources, as well as from a database of captured real world illumination. We also reformulate the optimization criterion used in PCA. The resulting basis, we believe has higher representability and is better for analyzing images of shaded objects. The different bases are compared on a database of images to test the representability.

关键词： Lighting Light sources computer vision Principal component analysis Power harmonic filters Reflectivity Image databases Image analysis Jacobian matrices Low pass filters

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Simultaneous feature selection and classifier training via linear programming: a case study for face expression recognition

Simultaneous feature selection and classifier training via l...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Guodong Guo C.R. Dyer Computer Sciences Department University of Wisconsin Madison Madison WI USA

A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the classifier. Because traditional classification methods in computer vision have used a two-step approach: feature selection followed by classifier training, feature selection has often been ad hoc using heuristics or requiring a time-consuming forward and backward search process. Moreover, it is difficult to determine which features to use and how many features to use when these two steps are separated. The linear programming technique used in this paper, which we call feature selection via linear programming (FSLP), can determine the number of features and which features to use in the resulting classification function based on recent results in optimization. We analyze why FSLP can avoid the curse of dimensionality problem based on margin analysis. As one demonstration of the performance of this FSLP technique for computer vision tasks, we apply it to the problem of face expression recognition. recognition accuracy is compared with results using support vector machines, the AdaBoost algorithm, and a Bayes classifier.

关键词： Erbium computer aided software engineering Face recognition computer vision Linear programming pattern recognition Face detection Support vector machines Support vector machine classification Computational complexity

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Analyzing appearance and contour based methods for object categorization

Analyzing appearance and contour based methods for object ca...

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conference on computer vision and pattern recognition (cvpr)

作者： B. Leibe B. Schiele Perceptual Computing and Computer Vision Group ETH Zurich Switzerland

Object recognition has reached a level where we can identify a large number of previously seen and known objects. However, the more challenging and important task of categorizing previously unseen objects remains largely unsolved. Traditionally, contour and shape based methods are regarded most adequate for handling the generalization requirements needed for this task. Appearance based methods, on the other hand, have been successful in object identification and detection scenarios. Today little work is done to systematically compare existing methods and characterize their relative capabilities for categorizing objects. In order to compare different methods we present a new database specifically tailored to the task of object categorization. It contains high-resolution color images of 80 objects from 8 different categories, for a total of 3280 images. It is used to analyze the performance of several appearance and contour based methods. The best categorization result is obtained by an appropriate combination of different methods.

关键词： Object recognition Shape computer vision Image databases Performance analysis Face detection Image segmentation Psychology Humans Object detection

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Adaptive pattern discovery for interactive multimedia retrieval

Adaptive pattern discovery for interactive multimedia retrie...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Yimin Wu Aidong Zhang Department of Computer Science and Engineering SUNY USA

ISBN: (纸本)0769519008

Relevance feedback has been an indispensable component for multimedia retrieval systems. In this paper, we present an adaptive pattern discovery method, which addresses relevance feedback by interactively discovering meaningful patterns of relevant objects. To facilitate pattern discovery, we first present a dynamic feature extraction method, which aims to alleviate the curse of dimensionality by extracting a feature subspace using balanced information gain. In the feature subspace, we train an online pattern classification method called adaptive random forests to classify multimedia objects as relevant or irrelevant. Our adaptive random forests adapts the traditional classification method known as random forests for relevance feedback. It improves the efficiency of pattern discovery by choosing the most-informative samples for online learning. Extensive experiments are carried out on a Corel image set (with 31,438 images) to evaluate the performance of our method as compared against the state-of-the-art approaches.

关键词： Feedback Feature extraction Image retrieval Machine learning pattern recognition Support vector machines Classification tree analysis Information retrieval Support vector machine classification Decision trees

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A variational framework for image segmentation combining motion estimation and shape regularization

A variational framework for image segmentation combining mot...

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conference on computer vision and pattern recognition (cvpr)

作者： D. Cremers Department of Computer Science University of California Los Angeles CA USA

Based on a geometric interpretation of the optic flow constraint equation, we propose a conditional probability on the spatio-temporal image gradient. We consistently derive a variational approach for the segmentation of the image domain into regions of homogeneous motion. The proposed energy functional extends the Mumford-Shah functional from gray value segmentation to motion segmentation. It depends on the spatio-temporal image gradient calculated from only two consecutive images of an image sequence. Moreover, it depends on motion vectors for a set of regions and a boundary separating these regions. In contrast to most alternative approaches, the problems of motion estimation and motion segmentation are jointly solved by minimizing a single functional. Numerical evaluation with both explicit and implicit (level set based) representations of the boundary shows the strengths and limitations of our approach.

关键词： Image segmentation Motion estimation Shape Motion segmentation computer vision Geometrical optics Image motion analysis Equations Image sequences Level set

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