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Multilinear independent components analysis

Multilinear independent components analysis

引用

conference on computer vision and pattern recognition (cvpr)

作者： M.A.O. Vasilescu D. Terzopoulos Department of Computer Science University of Toronto Toronto ONT Canada Courant Institute of Mathematical Sciences New York University New York NY USA

Independent components analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the different factors, or modes, inherent to image formation, including scene structure, illumination, and imaging. We introduce a nonlinear, multifactor model that generalizes ICA. Our multilinear ICA (MICA) model of image ensembles learns the statistically independent components of multiple factors. Whereas ICA employs linear (matrix) algebra, MICA exploits multilinear (tensor) algebra. We furthermore introduce a multilinear projection algorithm which projects an unlabeled test image into the N constituent mode spaces to simultaneously infer its mode labels. In the context of facial image ensembles, where the mode labels are person, viewpoint, illumination, expression, etc., we demonstrate that the statistical regularities learned by MICA capture information that, in conjunction with our multilinear projection algorithm, improves automatic face recognition.

关键词： Independent component analysis Lighting Principal component analysis Face recognition Algebra Projection algorithms Testing Higher order statistics Layout Matrices

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Are External Face Features Useful for Automatic Face Classification?

Are External Face Features Useful for Automatic Face Classif...

引用

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

作者： A. Lapedriza D. Masip J. Vitria Computer Vision Center (CVC) & Department Informàtica Universitat Autònoma Barcelona Bellaterra Spain

In this paper a new experiment using the FRGC database is proposed. The experiment deals with the use of external face features for face classification. Unlike the most part of algorithms that can be found in the literature for classifying faces, we consider the external information located at hair and ears as a reliable source of information. These features have often been discarded due to the difficulty of their extraction and alignment, and the lack of robustness in security related applications. Nevertheless, there are a lot of applications where these considerations are not valid, and the proper processing of external features can be an important additional source of information for classifications tasks. We also propose, following this assumption, a method for extracting external information from face images. The method is based on a top-down reconstructionbased algorithm for extracting the external face features. Once extracted, they are encoded in a second step using the Non Negative Matrix Factorization (NMF) algorithm, yielding an aligned high dimensional feature vector. This method has been used in a gender recognition problem, concluding that the encoded information is useful for classification purposes.

关键词： Face detection Data mining Face recognition Hair Information resources computer vision Humans Spatial databases Ear Robustness

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A Review on vision-Based Full DOF Hand Motion Estimation

A Review on Vision-Based Full DOF Hand Motion Estimation

引用

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

作者： A. Erol G. Bebis M. Nicolescu R.D. Boyle X. Twombly Computer Vision Laboratory University of Nevada Reno NV USA Bio Vis Laboratory NASA Ames Research Center Moffett Field CA USA

Direct use of the hand as an input device is an attractive method for providing natural human-computer interaction (HCI). Currently, the only technology that satisfies the advanced requirements of hand-based input for HCI is glovebased sensing. This technology, however, has several drawbacks including that it hinders the ease and naturalness with which the user can interact with the computer controlled environment, and it requires long calibration and setup procedures. computer vision has the potential to provide much more natural, non-contact solutions. As a result, there have been considerable research efforts to use the hand as an input device for HCI. A very challenging problem in this context, which is the focus of this review, is recovering the 3D pose of the hand and the fingers as glove-based devices do. This paper presents a brief literature review on full degreeof- freedom (DOF) hand motion estimation methods.

关键词： Motion estimation Human computer interaction Fingers Application software Data mining computer vision Motion measurement Laboratories Space technology Calibration

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A two-stage level set evolution scheme for man-made objects detection in aerial images

A two-stage level set evolution scheme for man-made objects ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Guo Cao Xin Yang Zhihong Mao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai P.R. China

ISBN: (纸本)0769523722

A novel two-stage level set evolution method for detecting man-made objects in aerial images is described. The method is based on a modified Mumford-Shah model and it uses a two-stage curve evolution strategy to get a preferable detection. It applies fractal error metric, developed by Cooper, et al. (1994) at the first curve evolution stage and adds additional constraint texture edge descriptor that is defined by using DCT (discrete cosine transform) coefficients on the image at the next stage. Man-made objects and natural areas are optimally differentiated by evolving the partial differential equation. The method artfully avoids selecting a threshold to separate the fractal error image, while an improper threshold often results in great segmentation errors. Experiments of the segmentation show that the proposed method is efficient.

关键词： Level set Object detection Hidden Markov models Image segmentation Fractals Discrete cosine transforms pattern recognition Roads Layout Parameter estimation

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Estimation of Human Figure Motion Using Robust Tracking of Articulated Layers

Estimation of Human Figure Motion Using Robust Tracking of A...

引用

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

作者： Kooksang Moon V. Pavlovic Department of Computer Science Rutgers University Piscataway NJ USA

We propose a probabilistic method for tracking articulated objects, such as the human figure, across multiple layers in monocular image sequence. In this method, each link of a probabilistic articulated object is assigned to one individual image layer. The layered representation allows us to robustly model the pose and occlusion of object parts during its motion. Appearance of links is described in terms of learned statistics of basic image features, such as color, and geometric models of robust spatial kernels. This results in a highly efficient computational method for inference of the object’s pose. We apply this approach to tracking of the human figure in monocular video sequences. We show that the proposed method, coupled with a learned dynamic model, can lead to a robust articulated object tracker.

关键词： Motion estimation Humans Robustness Tracking Image sequences Kernel Focusing Parametric statistics Computational efficiency Biological system modeling

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Appearance modeling for tracking in multiple non-overlapping cameras

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

引用

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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Topological Mapping from Image Sequences

Topological Mapping from Image Sequences

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

作者： J. Mulligan G. Grudic Department of Computer Science University of Colorado Boulder Boulder CO USA

An autonomous agent should be able to traverse a new environment and construct a topological representation of what it has seen. We present two new semi-supervised learning techniques which allow us to segment extended sensor (image) sequences into a topological map by clustering on low-dimensional manifolds in sensor space. The general approach is based on outlier detection in manifold space, closely related to spectral clustering. The first technique fixes the s parameter of the affinity matrix, the second allows each cluster to optimize for a different s. In both cases manifold clusters can be associated with the user’s conceptual map by labelling one image per cluster. We demonstrate these techniques for indoor and outdoor sequences.

关键词： Image sequences Image sensors Navigation Semisupervised learning Labeling Sensor phenomena and characterization Autonomous agents Robot sensing systems Robot kinematics Orbital robotics

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Active polyhedron: surface evolution theory applied to deformable meshes

Active polyhedron: surface evolution theory applied to defor...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Slabaugh G. Unal Intelligent Vision and Reasoning Department Siemens Corporate Research Inc. Princeton NJ USA

This paper presents a novel 3D deformable surface that we call an active polyhedron. Rooted in surface evolution theory, an active polyhedron is a polyhedral surface whose vertices deform to minimize a regional and/or boundary-based energy functional. Unlike continuous active surface models, the vertex motion of an active polyhedron is computed by integrating speed terms over polygonal faces of the surface. The resulting ordinary differential equations (ODEs) provide improved robustness to noise and allow for larger time steps compared to continuous active surfaces implemented with level set methods. We describe an electrostatic regularization technique that achieves global regularization while better preserving sharper local features. Experimental results demonstrate the effectiveness of an active polyhedron in solving segmentation problems as well as surface reconstruction from unorganized points.

关键词： Surface reconstruction Ultrasonic imaging Image segmentation Noise robustness Active noise reduction Electrostatics Image reconstruction Deformable models Acoustic noise Speckle

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A Theory for Photometric Self-Calibration of Multiple Overlapping Projectors and Cameras

A Theory for Photometric Self-Calibration of Multiple Overla...

引用

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

作者： Peng Song Tat-Jen Cham School of Computer Engineering Nanyang Technological University Singapore Singapore-Massachusetts Institute of Technology Alliance Singapore

A theory for photometric calibration of cameras and multiple projectors with overlapping displays is presented. The theory is predominantly based on the analysis of isointensity curves in projector input state space curves which define different projector input intensity combinations that result in the same camera-observed pixel intensities. Three methods, which have different speed and accuracy tradeoffs, are proposed for recovering the projector-to-screen and screento- camera intensity transfer functions. The methods do not require a specific parametric model for the shapes of these functions, nor impose any smoothness constraints. Additional methods are described for calibrating projector offsets and binary light sources, and also extending the perpixel analysis to other pixels in the display. The methods do not require the use of expensive equipment, and may be carried out with a low dynamic range camera with minimal controls.

关键词： Photometry Cameras Displays Calibration State-space methods Transfer functions Parametric statistics Shape Light sources Dynamic range

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Spatial priors for part-based recognition using statistical models

Spatial priors for part-based recognition using statistical ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Crandall P. Felzenszwalb D. Huttenlocher Cornell University USA The Univerisity of Chicago USA Cornell University

We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These models provide a way of relating different spatial priors that have been used for recognizing generic classes of objects, including joint Gaussian models and tree-structured models. By providing explicit control over the degree of spatial structure, our models make it possible to study the extent to which additional spatial constraints among parts are actually helpful in detection and localization, and to consider the tradeoff in representational power and computational cost. We consider these questions for object classes that have substantial geometric structure, such as airplanes, faces and motorbikes, using datasets employed by other researchers to facilitate evaluation. We find that for these classes of objects, a relatively small amount of spatial structure in the model can provide statistically indistinguishable recognition performance from more powerful models, and at a substantially lower computational cost.

关键词： Computational efficiency Face detection Tree graphs Object recognition Object detection Computational complexity Graphical models Airplanes Motorcycles Humans

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