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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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Improving object classification in far-field video

Improving object classification in far-field video

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conference on computer vision and pattern recognition (cvpr)

作者： B. Bose E. Grimson Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

Object classification in far-field video sequences is a challenging problem because of low-resolution imagery and projective image distortion. Most existing far-field classification systems are trained to work well in a constrained set of scenes, but can fail dramatically when applied to new scenes, or even different views of the same scene. We identify discriminative object features for classifying vehicles and pedestrians and develop a scene-invariant classification system that is trained on a small number of labeled examples from a few scenes, but transfers well to a wide range of new scenes. Simultaneously, we demonstrate that use of scene-specific context features (such as image position and direction of motion of objects) can greatly improve classification in any given scene. To combine these ideas, we propose a new algorithm for adapting a scene-invariant classifier to scene-specific features by retraining with the help of unlabelled data in a novel scene. Experimental results demonstrate the effectiveness of our context features and scene-transfer/adaptation algorithm for multiple urban and highway scenes.

关键词： Layout Cameras Video sequences Image resolution Road transportation Object detection Vehicle detection Humans Pixel computer science

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Asymmetrically boosted HMM for speech reading

Asymmetrically boosted HMM for speech reading

引用

conference on computer vision and pattern recognition (cvpr)

作者： Pei Yin I. Essa J.M. Rehg GVU Center / College of Computing Georgia Institute of Technology Atlanta GA USA

Speech reading, also known as lip reading, is aimed at extracting visual cues of lip and facial movements to aid in recognition of speech. The main hurdle for speech reading is that visual measurements of lip and facial motion lack information-rich features like the Mel frequency cepstral coefficients (MFCC), widely used in acoustic speech recognition. These MFCC are used with hidden Markov models (HMM) in most speech recognition systems at present. Speech reading could greatly benefit from automatic selection and formation of informative features from measurements in the visual domain. These new features can then be used with HMM to capture the dynamics of lip movement and eventual recognition of lip shapes. Towards this end, we use AdaBoost methods for automatic visual feature formation. Specifically, we design an asymmetric variant of AdaBoost M2 algorithm to deal with the ill-posed multi-class sample distribution inherent in our problem. Our experiments show that the boosted HMM approach outperforms conventional AdaBoost and HMM classifiers. Our primary contributions are in the design of (a) boosted HMM and (b) asymmetric multi-class boosting.

关键词： Hidden Markov models Speech recognition Mel frequency cepstral coefficient Acoustic measurements Face recognition Frequency measurement Motion measurement Shape Algorithm design and analysis Boosting

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Minimum effective dimension for mixtures of subspaces: a robust GPCA algorithm and its applications

Minimum effective dimension for mixtures of subspaces: a rob...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Kun Huang Yi Ma R. Vidal Department of Electrical & Computer Engineering University of Illinois Urbana-Champaign Urbana-Champaign IL USA Department Biomedical Engineering Johns Hopkins University Baltimore MD USA

We propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection criteria typically assume that data can be modelled with a parametric model of certain (possibly differing) dimension and a known error distribution. However, for mixtures of subspaces with different dimensions, a generalized notion of dimensionality is needed and hence introduced in this paper. The proposed MED criterion minimizes this geometric dimension subject to a given error tolerance (regardless of the noise distribution). Furthermore, combined with a purely algebraic approach to clustering mixtures of subspaces, namely the generalized PCA (GPCA), the MED is designed to also respect the global algebraic and geometric structure of the data. The result is a non-iterative algorithm called robust GPCA that estimates from noisy data an unknown number of subspaces with unknown and possibly different dimensions subject to a maximum error bound. We test the algorithm on synthetic noisy data and in applications such as motion/image/video segmentation.

关键词： Image segmentation Principal component analysis Application software Noise robustness computer vision Maximum likelihood estimation Solid modeling Biomedical engineering Parametric statistics Clustering algorithms

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A minimal solution to the generalised 3-point pose problem

A minimal solution to the generalised 3-point pose problem

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Nister Sarnoff Corporation Princeton NJ USA

It is a well known classical result that given the image projections of three known world points it is possible to solve for the pose of a calibrated perspective camera to up to four pairs of solutions. We solve the generalised problem where the camera is allowed to sample rays in some arbitrary but known fashion and is not assumed to perform a central perspective projection. That is, given three back-projected rays that emanate from a camera or multi-camera rig in an arbitrary but known fashion, we seek the possible poses of the camera such that the three rays meet three known world points. We show that the generalised problem has up to eight solutions that can be found as the intersections between a circle and a ruled quartic surface. A minimal and efficient constructive numerical algorithm is given to find the solutions. The algorithm derives an octic polynomial whose roots correspond to the solutions. In the classical case, when the three rays are concurrent, the ruled quartic surface and the circle possess a reflection symmetry such that their intersections come in symmetric pairs. This manifests itself in that the odd order terms of the octic polynomial vanish. As a result, up to four pairs of solutions can be found in closed form. The proposed algorithm can be used to solve for the pose of any type of calibrated camera or camera rig. The intended use for the algorithm is in a hypothesise-and-test architecture.

关键词： Cameras Polynomials Reflection computer vision Geometry Collaboration Government computer architecture Solid modeling Mirrors

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Linear sequence-to-sequence alignment

Linear sequence-to-sequence alignment

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conference on computer vision and pattern recognition (cvpr)

作者： R.L. Carceroni F.L.C. Padua G.A.M.R. Santos K.N. Kutulakos Department de Ciência da Computação Universidade Federal de Minas Gerais Belo Horizonte Minas Gerais Brazil Department of Computer Science University of Toronto Toronto Canada

We present a novel approach for temporally aligning N unsynchronized sequences of a dynamic 3D scene, captured from distinct viewpoints. Unlike existing methods, which work for N = 2 and rely on a computationally-intensive search in the space of temporal alignments, we reduce the problem for general N to the robust estimation of a single line in RN. This line captures all temporal relations between the sequences and can be computed without any prior knowledge of these relations. Experimental results show that our method can accurately align sequences even when they have large mis-alignments (e.g., hundreds of frames), when the problem is seemingly ambiguous (e.g., scenes with roughly periodic motion), and when accurate manual alignment is difficult (e.g., due to slow-moving objects).

关键词： Layout Video recording Video sequences Robustness Cameras Tracking Computational geometry computer science Surveillance Metrology

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Tomographic reconstruction of piecewise smooth images

Tomographic reconstruction of piecewise smooth images

引用

conference on computer vision and pattern recognition (cvpr)

作者： C.V. Alvino A.J. Yezzi School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

In computed tomography, direct inversion of the Radon transform requires more projections than are practical due to constraints in scan time and image accessibility. Therefore, it is necessary to consider the estimation of reconstructed images when the problem is under-constrained, i.e., when a unique solution does not exist. To resolve ambiguities among solutions, it is necessary to place additional constraints on the reconstructed image. In this paper, we present a surface evolution technique to model the reconstructed image as piecewise smooth. We model the reconstructed image as two regions that are each smoothly varying in intensity and are separated by a smooth surface. We define a cost functional to penalize deviation from piecewise smoothness while ensuring that the projections of the estimated image match the measured projections. From this functional, we derive an evolution for the modeled image intensity and an evolution for the surface, thereby defining a variational tomographic estimation technique. We show example reconstructions to highlight the performance of the proposed method on real medical images.

关键词： Image reconstruction Surface reconstruction Active contours Computed tomography Cost function Image segmentation Time factors Image resolution Biomedical imaging Reconstruction algorithms

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Efficient graphical models for processing images

Efficient graphical models for processing images

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conference on computer vision and pattern recognition (cvpr)

作者： M.F. Tappen B.C. Russell W.T. Freeman Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

Graphical models are powerful tools for processing images. However, the large dimensionality of even local image data poses a difficulty. Representing the range of possible graphical model node variables with discrete states leads to an overwhelmingly large number of states for the model, often making both exact and approximate inference computationally intractable. We propose a representation that allows a small number of discrete states to represent the large number of possible image values at each pixel or local image patch. Each node in the graph represents the best regression function, chosen from a set of candidate functions, for estimating the unobserved image pixels from the observed samples. This permits a small number of discrete states to summarize the range of possible image values at each point in the image. Belief propagation is then used to find the best regressor to use at each point. To demonstrate the usefulness of this technique, we apply it to two problems: super-resolution and color demosaicing. In both cases, we find our method compares well against other techniques for these problems.

关键词： Graphical models Pixel Belief propagation Statistics computer science Artificial intelligence Laboratories Layout Gray-scale Inference algorithms

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Motion estimation by Swendsen-Wang Cuts

Motion estimation by Swendsen-Wang Cuts

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Barbu A. Yuille Computer Science Department University of California Los Angeles USA Statistics Department University of California Los Angeles USA

Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear, as well as motion and motion boundaries. We formulate the problem as probabilistic inference using prior models of images and the motion field. Secondly, it introduces a new algorithm for motion estimation based on Swendsen-Wang Cuts, which performs inference on the image sequence model using bottom-up proposals to guide the search. The algorithm proceeds by first estimating the motion without the boundaries, and then by clustering in the velocity space to obtain initial estimates of the motion boundaries. The algorithm performs MAP estimation by evolving the motion boundaries by a stochastic boundary diffusion algorithm, while improving the motion estimates. Our approach is illustrated on real images of city scenes and on simulated data and can deal with large motions (even 10 pixels or more per frame). We show a brief comparison of Swendsen-Wang Cuts with Graph Cuts and Belief Propagation on the related stereo matching problem.

关键词： Motion estimation Clustering algorithms Inference algorithms Image sequences Image coding Proposals Stochastic processes Cities and towns Layout Pixel

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MetaMorphs: Deformable shape and texture models

MetaMorphs: Deformable shape and texture models

引用

conference on computer vision and pattern recognition (cvpr)

作者： Xiaolei Huang D. Metaxas Ting Chen Division of Computer and Information Sciences Rutgers University New Brunswick NJ USA

We present a new class of deformable models, MetaMorphs, that consist of both shape and interior texture. The model deformations are derived from both boundary and region information in a common variational framework. This framework represents a generalization of previous model-based segmentation approaches. The shapes of the new models are represented implicitly as "images" in the higher dimensional space of distance transforms. The interior textures are captured using a nonparametric kernel-based approximation of the intensity probability density functions (p.d.f.s) inside the models. The deformations that MetaMorph models can undergo are defined using a space warping technique - the cubic B-spline based Free Form Deformations (FFD). When using the models for boundary finding in images, we derive the model dynamics from an energy functional consisting of both edge energy terms and intensity/texture energy terms. This way, the models deform wider the influence of forces derived from both boundary and regional information. The proposed MetaMorph deformable models are efficient in convergence, have large attraction range, and are robust to image noise and inhomogeities. Various examples on finding object boundaries in noisy images with complex textures demonstrate the potential of the proposed technique.

关键词： Shape Deformable models Image segmentation computer vision Biomedical imaging Active contours Level set Probability density function Spline Convergence

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Modeling complex motion by tracking and editing hidden Markov graphs

Modeling complex motion by tracking and editing hidden Marko...

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conference on computer vision and pattern recognition (cvpr)

作者： Yizhou Wang Song Chun Zhu Computer Science Department University of California Los Angeles USA Department of Statistics University of California Los Angeles USA

We propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four components: (1) A photometric model using primal sketch[8] which transfers an image into an attribute graph representation. Each vertex of the graph is a scaled and oriented image patch selected from a dictionary. The graph connects and aligns these patches. (2) A geometric model which characterizes the deformation of the attribute graph. (3) A dynamic model, which specifies the motion dynamics of these vertices (patches) and their interactions in the form of coupled Markov chains. (4) A topological model, which interprets the graph topological changes over time. We learn this generative model by a stochastic gradient algorithm implemented by Markov Chain Monte Carlo (MCMC) sampling. This method is shown to be effective in handling the topological changes of graphs. The correctness of the learned model is verified by the low-dimension reconstruction of the original image as well as by the realistic motion sequences it synthesized.

关键词： Hidden Markov models Tracking Solid modeling Deformable models Rivers Fires Photometry Dictionaries Stochastic processes Monte Carlo methods

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