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Ontology-Driven Bayesian Networks for Dynamic Scene Understanding

Ontology-Driven Bayesian Networks for Dynamic Scene Understa...

引用

ieee computer Society Conference on computer vision and Pattern Recognition workshops (CVPRW)

作者： C. Town Computer Laboratory University of Cambridge Cambridge UK

This paper describes how an ontology consisting of a ground truth schema and a set of annotated training sequences can be used to train the structure and parameters of Bayesian networks for event recognition. It is shown how the performance of such networks can be improved by augmenting the original ontology with visual object detection, appearance modelling and tracking methods. The integration of these different sources of evidence is optimised with reference to the syntactic and semantic constraints of the ontology. Through the application of these techniques to a visual surveillance problem, it is shown how high-level event, object and scenario properties may be inferred on the basis of the visual content descriptors and an ontology of states, roles, situations and scenarios which is derived from a pre-defined ground truth schema. Performance analysis of the resulting framework allows alternative ontologies to be compared for their self-consistency and realisability in terms of the different visual detection and tracking modules.

关键词： Ontologies Bayesian methods Layout Surveillance Performance analysis computer vision Object detection Data mining Cities and towns computer networks

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Stereoscopic shading: integrating multi-frame shape cues in a variational framework

Stereoscopic shading: integrating multi-frame shape cues in ...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： H. Jin A. Yezzi S. Soatto Washington University St Lucia MO USA

We address the problem of integrating multi-frame stereo and shading cues within the framework of optimization in the infinite-dimensional space of piecewise smooth surfaces. Cue integration then reduces to the determination of regions where prior assumptions on the reflectance of the surfaces can be enforced. By combining cues, our formulation allows defining a well-posed problem even when reconstruction from stereo or shading in isolation would be ill-posed. For a simplified model we prove the necessary conditions for optimality, and propose an iterative optimization algorithm, which we implement using ultra-narrowband level set methods.

关键词： Shape Bismuth

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Learning to Detect Scene Text Using a Higher-Order MRF with Belief Propagation

Learning to Detect Scene Text Using a Higher-Order MRF with ...

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ieee computer Society Conference on computer vision and Pattern Recognition workshops (CVPRW)

作者： Dong-Qing Zhang Shih-Fu Chang Department of Electrical Engineering Columbia University New York NY USA

Detecting text in natural 3D scenes is a challenging problem due to background clutter and photometric/gemetric variations of scene text. Most prior systems adopt approaches based on deterministic rules, lacking a systematic and scalable framework. In this paper, we present a parts-based approach for 3D scene text detection using a higher-order MRF model. The higher-order structure is used to capture the spatial-feature relations among multiple parts in scene text. The use of higher-order structure and the feature-dependent potential function represents significant departure from the conventional pairwise MRF, which has been successfully applied in several low-level applications. We further develop a variational approximation method, in the form of belief propagation, for inference in the higher-order model. Our experiments using the ICDAR'03 benchmark showed promising results in detecting scene text with significant geometric variations, background clutter on planar surfaces or non-planar surfaces with limited angles.

关键词： Layout Belief propagation Object detection Biological system modeling Application software Tree graphs Humans computer vision Photometry Approximation methods

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Adaptive quantization of color space for recognition of finished wooden components

Adaptive quantization of color space for recognition of fini...

引用

ieee workshop on Applications of computer vision (WACV)

作者： A.L. Abbott Y. Zhao The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

The paper concerns the recognition of textured objects, such as stained wooden parts, using color images. Many existing color classification systems utilize histogram-based similarity measures to compare an observed image with models from a database. Although the performance of these systems depends heavily on proper quantization of the color space, most quantization methods are based on traditional clustering or thresholding operations. The authors describe a novel approach to color space quantization in which the intersection of meaningful representations results in a partition of the color space. The color descriptions are chosen adaptively, using a set of training images. The resulting partition serves as the domain for histograms of models and of observed images and information-theoretic similarity measures are used to perform recognition. The motivation for this system is to achieve high recognition accuracy in an industrial setting. Laboratory tests have demonstrated a high level of accuracy for this technique, even though the objects of interest exhibit large variations of texture and color.

关键词： Quantization Histograms Image recognition Image color analysis Image databases Industrial training Laboratories Testing Image analysis Performance evaluation

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Efficient Model Evaluation with Bilinear Separation Model

Efficient Model Evaluation with Bilinear Separation Model

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ieee workshop on Applications of computer vision (WACV)

作者： Fanyi Xiao Martial Hebert Robotics Institute Carnegie Mellon University

ISBN: (纸本)9781479966844

In this paper, we investigate the issue of evaluating efficiently a large set of models on an input image in detection and classification tasks. We show that by formulating the visual task as a large matrix multiplication problem, something that is possible for a broad set of modern detectors and classifiers, we are able to dramatically reduce the rate of growth of computation as the number of models increases. The approach, based on a bilinear separation model, combines standard matrix factorization with a task dependent term which ensures that the resulting smaller size problem maintains performance on the original task. Experiments show that we are able to maintain, or even exceed, the level of performance compared to the default approach of using all the models directly, in both detection and classification tasks. This approach is complementary to other efforts in the literature on speeding up computation through GPU implementation, fast matrix operations, or quantization, in that any of these optimizations can be incorporated.

关键词： Computational modeling Approximation methods Object detection Data models Predictive models Feature extraction Testing

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Surface reconstruction by integrating 3D and 2D data of multiple views

Surface reconstruction by integrating 3D and 2D data of mult...

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International Conference on computer vision (ICCV)

作者： Lhuillier Long Quan CNRS Universite Blaise Pascal France Department of Computer Scince Hong Kong University of Science and Technology Hong Kong China

Surface representation is needed for almost all modeling and visualization applications, but unfortunately, 3D data from a passive vision system are often insufficient for a traditional surface reconstruction technique that is designed for densely scanned 3D point data. In this paper, we develop a new method for surface reconstruction by combining both 3D data and 2D image information. The silhouette information extracted from 2D images can also be integrated as an option if it is available. The new method is a variational approach with a new functional integrating 3D stereo data with 2D image information. This gives a more robust approach than existing methods using only pure 2D information or 3D stereo data. We also propose a bounded regularization method to implement efficiently the surface evolution by level-set methods. The properties of the algorithms are discussed, proved for some cases, and empirically demonstrated through intensive experiments on real sequences.

关键词： Surface reconstruction Image reconstruction Stereo vision Surface fitting computer vision Layout Data visualization Application software Cameras Deformable models

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Locating texture boundaries using a fast unsupervised approach based on clustering algorithms fusion and level set

Locating texture boundaries using a fast unsupervised approa...

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ieee International Conference on Signal and Image Processing Applications (ICSIPA)

作者： Mehryar Emambakhsh Mohammad Hossein Sedaaghi Hossein Ebrahimnezhad Computer Vision Laboratory Department of Electrical Engineering Sahand University of Technology Tabriz Iran Department of Electrical Engineering Sahand University of Technology Tabriz Iran

Image segmentation deals with partitioning an input image into disjoint/non-overlapping regions. Among different segmentation algorithms, level set methods have been very popular. Less sensitivity to initialization, ability to split and merge the contour, and also, involving statistical inference have made level set even more accepted than similar methods like snakes. However, it is very time-consuming. To solve this problem, in this paper a fast variational approach is presented for texture segmentation. For this purpose, first a feature space based on non-linear diffusion is set up from CIE L*a*b* colour components. Then, this feature space is clustered by fusion of clustering algorithms. Finally, the produced cluster map is used in level set for contour evolution. As it is shown in the simulation results, our algorithm is robust in segmenting noisy texture. Also, it is faster than previous level set approaches for texture segmentation.

关键词： Clustering algorithms level set Image segmentation Partitioning algorithms Robustness Cities and towns Biomedical imaging Diffusion tensor imaging Signal processing Image processing

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Stereoscopic segmentation

Stereoscopic segmentation

引用

International Conference on computer vision (ICCV)

作者： A.J. Yezzi S. Soatto Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Washington University Saint Louis USA Computer Science University of California Los Angeles Los Angeles CA USA

ISBN: (纸本)0769511430

We cast the problem of multiframe stereo reconstruction of a smooth shape as the global region segmentation of a collection of images of the scene. Dually, the problem of segmenting multiple calibrated images of an object becomes that of estimating the solid shape that gives rise to such images. We assume that the radiance has smooth statistics. This assumption covers Lambertian scenes with smooth or constant albedo as well as fine homogeneous textures, which are known challenges to stereo algorithms based on local correspondence. We pose the segmentation problem within a variational framework, and use fast level set methods to approximate the optimal solution numerically. Our algorithm does nor work in the presence of strong textures, where traditional reconstruction algorithms do. It enjoys significant robustness to noise under the assumptions it is designed for.

关键词： Image segmentation Shape Layout Stereo image processing Image reconstruction Solids Statistics level set Reconstruction algorithms Noise robustness

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A level-set based approach to image registration

A level-set based approach to image registration

引用

workshop on Mathematical methods in Biomedical Image Analysis

作者： B.C. Vemuri J. Ye Y. Chen C.M. Leonard Department of CISE University of Florida Gainesville FL USA Department of Mathematics University of Florida Gainesville FL USA Department of Neuroscience University of Florida Gainesville FL USA

Image registration is an often encountered problem in various fields including medical imaging, computer vision and image processing. Here, the authors present a novel curve evolution approach expressed in a level-set framework to achieve image registration. The key features of the authors' algorithm are, (a) it can account for small and large deformations, (b) it is very fast (unlike most large deformation schemes) and (c) existence and uniqueness of the solution for the evolution model has been established in a Sobolev space. The authors demonstrate the implementation results on a variety of images including synthetic and real data.

关键词： Image registration Computed tomography

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Segmentation of Neighboring Structures by Modeling Their Interaction

Segmentation of Neighboring Structures by Modeling Their Int...

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ieee computer Society Conference on computer vision and Pattern Recognition workshops (CVPRW)

作者： Pingkun Yan Mubarak Shah School of Computer Science University of Central Florida USA

The similarity of pixel intensities, presence of noise, existence of partial volume effect and so on make segmentation of neighboring structures in medical image a challenging task. In this paper, we present a novel approach for segmenting multiple neighboring organs simultaneously by modeling interaction between them. Our method is motivated by the observation that radiologists mark ambiguous boundaries by considering all surrounding anatomic structures. In the proposed interaction model, the connectedness, competition and repulsion between organs are analyzed. By quantitatively defining these interaction components, an energy functional is formulated and structures are obtained by minimizing the energy. An energy minimization algorithm based on multiway graph cuts is proposed, which obtains an approximation within a known factor of the global minimum. The promising experimental results on various medical images demonstrate the performance of our segmentation algorithm.

关键词： Image segmentation Deformable models Biomedical imaging level set Minimization methods Anatomical structure computer vision Topology computer science Pixel

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