Energy Minimization Methods in Computer Vision and Pattern Recognition [electronic resource] :6th International Conference, EMMCVPR 2007, Ezhou, China, August 27-29, 2007. Proceedings /
Contributor(s): Yuille, Alan L [editor.] | Zhu, Song-Chun [editor.] | Cremers, Daniel [editor.] | Wang, Yongtian [editor.] | SpringerLink (Online service).Material type: BookSeries: Lecture Notes in Computer Science: 4679Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.Description: XII, 500 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540741985.Subject(s): Computer science | Algorithms | Data mining | Artificial intelligence | Computer graphics | Image processing | Pattern recognition | Computer Science | Image Processing and Computer Vision | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Computer Graphics | Algorithm Analysis and Problem Complexity | Data Mining and Knowledge DiscoveryOnline resources: Click here to access online
Algorithms -- 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 Object Recognition, 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.
This 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.