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024 7 _a10.1007/978-3-540-74198-5
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245 1 0 _aEnergy Minimization Methods in Computer Vision and Pattern Recognition
_h[electronic resource] :
_b6th International Conference, EMMCVPR 2007, Ezhou, China, August 27-29, 2007, Proceedings /
_cedited by Alan L. Yuille, Song-Chun Zhu, Daniel Cremers, Yongtian Wang.
250 _a1st ed. 2007.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2007.
300 _aXII, 500 p.
_bonline resource.
336 _atext
_btxt
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337 _acomputer
_bc
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338 _aonline resource
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347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v4679
505 0 _aAlgorithms -- An Effective Multi-level Algorithm Based on Simulated Annealing for Bisecting Graph -- Szemerédi's Regularity Lemma and Its Applications to Pairwise Clustering and Segmentation -- Exact Solution of Permuted Submodular MinSum Problems -- Efficient Shape Matching Via Graph Cuts -- Simulating Classic Mosaics with Graph Cuts -- An Energy Minimisation Approach to Attributed Graph Regularisation -- Applications to Faces and Text -- A Pupil Localization Algorithm Based on Adaptive Gabor Filtering and Negative Radial Symmetry -- Decomposing Document Images by Heuristic Search -- CIDER: Corrected Inverse-Denoising Filter for Image Restoration -- Skew Detection Algorithm for Form Document Based on Elongate Feature -- Active Appearance Models Fitting with Occlusion -- Combining Left and Right Irises for Personal Authentication -- Image Parsing -- Bottom-Up Recognition and Parsing of the Human Body -- to a Large-Scale General Purpose Ground Truth Database: Methodology, Annotation Tool and Benchmarks -- An Automatic Portrait System Based on And-Or Graph Representation -- Object Category Recognition Using Generative Template Boosting -- Bayesian Inference for Layer Representation with Mixed Markov Random Field -- Image Processing -- Dichromatic Reflection Separation from a Single Image -- Noise Removal and Restoration Using Voting-Based Analysis and Image Segmentation Based on Statistical Models -- A Boosting Discriminative Model for Moving Cast Shadow Detection -- Motion Analysis -- An a Contrario Approach for Parameters Estimation of a Motion-Blurred Image -- Improved Object Tracking Using an Adaptive Colour Model -- Vehicle Tracking Based on Image Alignment in Aerial Videos -- Probabilistic Fiber Tracking Using Particle Filtering and Von Mises-Fisher Sampling -- Compositional ObjectRecognition, Segmentation, and Tracking in Video -- Bayesian Order-Adaptive Clustering for Video Segmentation -- Dynamic Feature Cascade for Multiple Object Tracking with Trackability Analysis -- Shape Analysis -- Discrete Skeleton Evolution -- Shape Classification Based on Skeleton Path Similarity -- Removing Shape-Preserving Transformations in Square-Root Elastic (SRE) Framework for Shape Analysis of Curves -- Shape Analysis of Open Curves in ?3 with Applications to Study of Fiber Tracts in DT-MRI Data -- Three-Dimensional Processing -- Energy-Based Reconstruction of 3D Curves for Quality Control -- 3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes -- Continuous Global Optimization in Multiview 3D Reconstruction -- A New Bayesian Method for Range Image Segmentation -- Marked Point Process for Vascular Tree Extraction on Angiogram -- Surface Reconstruction from LiDAR Data with Extended Snake Theory.
520 _aThis volume contains the papers presented at the Sixth International Conference on Energy Minimization Methods on Computer Vision and Pattern Recognition (EMMCVPR 2007), held at the Lotus Hill Institute, Ezhou, Hubei, China, August 27-29, 2007. The motivation for this conference is the realization that many problems in computer vision and pattern recognition can be formulated in terms of probabilistic inference or optimization of energy functions. EMMCVPR 2007 addressed the critical issues of representation, learning, and inference. Important new themes include pr- abilistic grammars, image parsing, and the use of datasets with ground-truth to act as benchmarks for evaluating algorithms and as a way to train learning algorithms. Other themes include the development of efficient inference algorithms using advanced techniques from statistics, computer science, and applied mathematics. We received 140 submissions for this workshop. Each paper was reviewed by three committee members. Based on these reviews we selected 22 papers for oral presen- tion and 15 papers for poster presentation. This book makes no distinction between oral and poster papers. We have organized these papers in seven sections on al- rithms, applications, image parsing, image processing, motion, shape, and thr- dimensional processing. Finally, we thank those people who helped make this workshop happen. We - knowledge the Program Committee for their help in reviewing the papers.
650 0 _aComputer vision.
_9156918
650 0 _aPattern recognition systems.
_93953
650 0 _aArtificial intelligence.
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650 0 _aComputer graphics.
_94088
650 0 _aAlgorithms.
_93390
650 0 _aData mining.
_93907
650 1 4 _aComputer Vision.
_9156919
650 2 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Graphics.
_94088
650 2 4 _aAlgorithms.
_93390
650 2 4 _aData Mining and Knowledge Discovery.
_9156920
700 1 _aYuille, Alan L.
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700 1 _aZhu, Song-Chun.
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700 1 _aCremers, Daniel.
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700 1 _aWang, Yongtian.
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_9156924
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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