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Modeling Images of Natural 3D Surfaces: Overview and Potential Applications

Modeling Images of Natural 3D Surfaces: Overview and Potenti...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： A. Jalobeanu F.O. Kuehnel J.C. Stutz NASA Ames Research Center RIACS Moffett Field CA USA

Generative models of natural images have long been used in computer vision. However, since they only describe the statistics of 2D scenes, they fail to capture all the properties of the underlying 3D world. Even though such models are sufficient for many vision tasks, a 3D scene model is needed when it comes to inferring a 3D object or its characteristics. In this paper, we present such a generative model, incorporating both a multiscale surface prior model for surface geometry and reflectance, and an image formation process model based on realistic rendering, that accounts for the physics of image generation. We focus on the computation of the posterior model parameter densities, and on the critical aspects of the rendering. We also discuss how to efficiently invert the model within a Bayesian framework. We present a few potential applications, such as asteroid modeling and planetary topography recovery, illustrated by promising results on real images.

关键词： Surface topography Solid modeling Layout Rendering (computer graphics) Application software computer vision Statistics Geometry Reflectivity Physics

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Generating Mosaics with Minimum Distortions

Generating Mosaics with Minimum Distortions

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： D. Feldman A. Zomet School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem Israel Computer Science Department Columbia University New York NY USA

Manifold mosaicing is a fast and robust way to summarize video sequences captured by a moving camera. It is also useful for rendering compelling 3D visualizations from a video without estimating the 3D structure of the scene. However, since the result mosaics are not perspective images, their geometry is inherently distorted. These mosaics are commonly referred to as multi-perspective images, or multi-perspective mosaics. In this paper we address the following question: Given a video captured by a moving camera, what is the best multi-perspective mosaic that can be generated from it? What is the mosaic with the best combination of large field-of-view and minimal geometric distortions? We define the necessary conditions for a good mosaic and a quantitive criterion for the geometric distortions, and derive analytically the optimal mosaic under this criterion. Results on video sequences confirm that indeed the optimal mosaic has significantly better quality than those generated by other techniques.

关键词： Video sequences Cameras Layout Robustness Strips computer science Rendering (computer graphics) Visualization Image generation Manifolds

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Component-Based Face recognition with 3D Morphable Models

Component-Based Face Recognition with 3D Morphable Models

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： B. Weyrauch B. Heisele J. Huang V. Blanz Center for Biological and Computational Learning M.I.T. Cambridge MA USA Honda Research Institute USA Inc. Boston MA USA Max-Planck-Institute of Computer Science Saarbruecken Germany

We present a system for pose and illumination invariant face recognition that combines two recent advances in the computer vision field: 3D morphable models and component-based recognition. A 3D morphable model is used to compute 3D face models from three input images of each subject in the training database. The 3D models are rendered under varying pose and illumination conditions to build a large set of synthetic images. These images are then used for training a component-based face recognition system. The face recognition module is preceded by a fast hierarchical face detector resulting in a system that can detect and identify faces in video images at about 4 Hz. The system achieved a recognition rate of 88% on a database of 2000 real images of ten people, which is significantly better than a comparable global face recognition system. The results clearly show the potential of the combination of morphable models and component-based recognition towards pose and illumination invariant face recognition.

关键词： Face recognition Face detection Lighting Image databases Image recognition Biology computing computer vision Detectors Object detection Support vector machines

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Virtualized Classroom - Automated Production, Media Integration and User-Customized Presentation

Virtualized Classroom - Automated Production, Media Integrat...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Zhigang Zhu C. McKittrick Weihong Li Department of Computer Science City College City University of New York New York NY USA Department of Computer Science Graduate Center City University of New York New York NY USA

Multimedia materials from classrooms and seminars are rich sources of information. Our Virtualized Classroom Project, which is a testbed for integrating novel multimedia software systems, addresses fundamental research problems occurring in different components of a next-generation, processing-enhanced e-learning system. Our ultimate goal is to create a natural learning environment that could give students interactive experiences equivalent to, or even better than, the real classroom. This will be enabled by virtual instructor presence, user-selectable and fully-indexed visual aids, and flexible communications between students, the instructor and virtual instructors (computers). We have developed several basic components for the Virtualized Classroom project: automated data collection, intelligent media integration, and flexible user interfaces.

关键词： Production Electronic learning Cameras computer science Educational institutions Multimedia systems Seminars Information resources Software systems User interfaces

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Real-time 3D Surface Tracking and Its Applications

Real-time 3D Surface Tracking and Its Applications

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： N.A. Ramey J.J. Corso W.W. Lau D. Burschka G.D. Hager Computational Interaction and Robotics Laboratory Johns Hopkins University Baltimore MD USA

We present a general technique for directly estimating and tracking surfaces from a stream of rectified stereo pairs in real-time. These techniques are based on the iterative updating of surface representations directly from image information and use no disparity search except during initialization. We perform the tracking through an iteratively re-weighted least squares minimization wherein a mask is incorporated to increase robustness to occlusion. The algorithms are formulated for a general family of linear in parameters surface models and discussed for the cases of planar surfaces and tensor product surfaces. These algorithms have been implemented on standard hardware and run at or near frame rate, with accuracy on the order of 1/20 of a pixel. We discuss applications of the technique including mobile robot localization, general deforming surface tracking, and biometry of biological surfaces.

关键词： Tracking Stereo vision Iterative algorithms Layout Surface texture Optical computing Robots Laboratories Streaming media Least squares methods

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Learning Chance Probability Functions for Shape Retrieval or Classification

Learning Chance Probability Functions for Shape Retrieval or...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： B.J. Super Computer Science Department University of Illinois Chicago USA

Several example-based systems for shape retrieval and shape classification directly match input shapes to stored shapes, without using class membership information to perform the matching. We propose a method for improving the accuracy of this type of system. First, the system learns a set of chance probability functions (CPFs). The CPFs estimate the probabilities of obtaining a query shape with particular distances from each training example by chance. The learned CPFs are used at runtime to rapidly estimate the chance probabilities of the observed distances between the actual query shape and the database shapes. These estimated probabilities are then used as a dissimilarity measure for shape retrieval and/or nearest-neighbor classification. The CPF learning method is parameter-free. Experimental evaluation demonstrates that: (1) chance probabilities yield higher accuracy than Euclidean distances; (2) the learned CPFs support fast matching; and (3) the CPF-based system outperforms prior systems on a standard benchmark test of retrieval accuracy.

关键词： Shape measurement Information retrieval Runtime Databases Impedance matching Benchmark testing System testing MPEG 7 Standard computer science Learning systems

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Understanding Images of Graphical User Interfaces: A New Approach to Activity recognition for Visual Surveillance

Understanding Images of Graphical User Interfaces: A New App...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Li Yu T.E. Boult Lehigh University Bethlehem PA USA University of Colorado Colorado Springs CO USA

A fundamental problem in surveillance systems is the specification of "activities of interest". While various activity recognition systems have been developed, they have used complex hand-coded representations. What is of interest to a particular surveillance system user can vary greatly, and the security forces using the system are not, in general, advanced computer users. This paper presents a novel paradigm for specifying and recognizing activities in a surveillance system by visualizing tracking results, and using computer vision techniques to interpret the images presented by their Graphical User Interfaces. Representation of activities of interest can be easily drawn by users. Not only is the drawing-based specification of activities of interest easier than previous approaches, but when a "rule" fires, it is easy to explain "why", by showing the operator the associated drawings. This approach also permits a new type of system integration, where we integrate the "display" of sensors rather than trying to develop a complex communication protocol. A user study is reviewed showing the proposed approach is thousands of time faster than HMMs for event definition while it is simultaneously more accurate in event recognition.

关键词： Graphical user interfaces Image recognition Surveillance computer security Visualization computer vision Fires Displays Sensor systems Protocols

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Precise Image Segmentation by Iterative EM-Based Approximation of Empirical Grey Level Distributions with Linear Combinations of Gaussians

Precise Image Segmentation by Iterative EM-Based Approximati...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： A.A. Farag A. El-Baz G. Gimel'farb CVIP Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA CITR Department of Computer Science University of Auckland Auckland New Zealand

A new algorithm for segmenting a multi-modal grey-scale image is proposed. The image is described as a sample of a joint Gibbs random field of region labels and grey values. To initialize the model, a multi-modal mixed empirical grey level density distribution is approximated with several linear combinations of Gaussians, one linear combination per region. Bayesian decisions involving Expectation-Maximization and genetic optimization techniques are used to sequentially estimate and refine parameters of the model, including the number of Gaussians for each region. The final estimates are more accurate than with conventional normal mixture models and result in more adequate region borders in the image. Experiments with simulated and real medical CT images confirm the accuracy of our approach.

关键词： Image segmentation Gaussian approximation Gaussian distribution Iterative algorithms Linear approximation Bayesian methods Genetics Parameter estimation Gaussian processes Medical simulation

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Significance of Elastic Properties in Physics-Based Nonrigid Motion Modeling, A Numerical Sensitivity Analysis

Significance of Elastic Properties in Physics-Based Nonrigid...

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yong Zhang D.B. Goldgof S. Sarkar Department of Computer Science & Engineering University of South Florida Tampa FL USA

Parameters used in the physical models for nonrigid motion simulation are often not known with high precision. It has been recognized that the commonly used assumptions about the parameters may have adverse effects on the modeling quality. We present an efficient sensitivity analysis method to assess the impact of those assumptions by examining the model’s response to the parameter perturbation. Numerical experiments with both synthetic and real models show that (1) the normalized sensitivity distribution can help determine the relative importance of different parameters; (2) the dimensional sensitivity is useful in the assessment of a particular parameter assumption; (3) the model is more sensitive at the property discontinuity (heterogeneity). The proposed sensitivity analysis method is general and can also be applied to the assessment of other types of assumptions such as nonlinearity and anisotropy.

关键词： Motion analysis Numerical models Sensitivity analysis Biological system modeling Computational modeling Anisotropic magnetoresistance Medical simulation Solid modeling Material properties Biological materials

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Learning a Synchronous MAP for Improved Face recognition

Learning a Synchronous MAP for Improved Face Recognition

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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： P.S. Penev Seelicon Research Princeton NJ USA

Maximum A posteriori Probability (MAP) is a machine-learning method for classification of objects by their visual representations, such as humans by the images of their faces. Multiple-class recognition can be rendered in a two-class problem, through the attempt to categorize image differences as more likely under either the between- or the within-class hypotheses. When Gaussian models are learned for these two probability densities, Principal Component Analysis (PCA) is used to estimate them. This procedure leaves open the choice for the dimensionalities at which the two models are estimated-a 2-parameter learning problem. Synchronous MAP (sMAP) is proposed here to reduce the complexity to a single dimension by learning a synchronization between the models on the basis of their power spectra. Experiments are reported on the standard, publicly available FERET fafb Sep96 test protocol that demonstrate sMAP results which are almost twice better than the previously reported (non-synchronous) MAP results, and also improve significantly over the previous state of the art-another subspace approach, based on Linear Discriminant Analysis (LDA).

关键词： Face recognition Principal component analysis Level set Support vector machines Independent component analysis Rendering (computer graphics) Linear discriminant analysis Prototypes Maximum likelihood estimation Humans

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