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Energy Minimization Methods in Computer Vision and Pattern Recognition

6th International Conference, EMMCVPR 2007, Ezhou, China, August 27-29, 2007, Proceedings

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. Alan L. Yuille
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  2. Song-Chun Zhu
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  3. Daniel Cremers
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  4. Yongtian Wang
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4679)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: EMMCVPR 2007.

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Table of contents (37 papers)

  1. Front Matter

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  2. Algorithms

    1. An Effective Multi-level Algorithm Based on Simulated Annealing for Bisecting Graph

      • Lingyu Sun, Ming Leng
      Pages 1-12

    2. Szemerédi’s Regularity Lemma and Its Applications to Pairwise Clustering and Segmentation

      • Anna Sperotto, Marcello Pelillo
      Pages 13-27

    3. Exact Solution of Permuted Submodular MinSum Problems

      • Dmitrij Schlesinger
      Pages 28-38

    4. Efficient Shape Matching Via Graph Cuts

      • Frank R. Schmidt, Eno Töppe, Daniel Cremers, Yuri Boykov
      Pages 39-54

    5. Simulating Classic Mosaics with Graph Cuts

      • Yu Liu, Olga Veksler, Olivier Juan
      Pages 55-70

    6. An Energy Minimisation Approach to Attributed Graph Regularisation

      • Zhouyu Fu, Antonio Robles-Kelly
      Pages 71-86

  3. Applications to Faces and Text

    1. A Pupil Localization Algorithm Based on Adaptive Gabor Filtering and Negative Radial Symmetry

      • Fei Xiong, Yi Zhang, Guilin Zhang
      Pages 87-96

    2. Decomposing Document Images by Heuristic Search

      • Dashan Gao, Yizhou Wang
      Pages 97-111

    3. CIDER: Corrected Inverse-Denoising Filter for Image Restoration

      • You-Wei Wen, Michael Ng, Wai-ki Ching
      Pages 112-126

    4. Skew Detection Algorithm for Form Document Based on Elongate Feature

      • Feng-ying Xie, Zhi-guo Jiang, Lei Wang
      Pages 127-136

    5. Active Appearance Models Fitting with Occlusion

      • Xin Yu, Jinwen Tian, Jian Liu
      Pages 137-144

    6. Combining Left and Right Irises for Personal Authentication

      • Xiangqian Wu, Kuanquan Wang, David Zhang, Ning Qi
      Pages 145-152

  4. Image Parsing

    1. Bottom-Up Recognition and Parsing of the Human Body

      • Praveen Srinivasan, Jianbo Shi
      Pages 153-168

    2. Introduction to a Large-Scale General Purpose Ground Truth Database: Methodology, Annotation Tool and Benchmarks

      • Benjamin Yao, Xiong Yang, Song-Chun Zhu
      Pages 169-183

    3. An Automatic Portrait System Based on And-Or Graph Representation

      • Feng Min, Jin-Li Suo, Song-Chun Zhu, Nong Sang
      Pages 184-197

    4. Object Category Recognition Using Generative Template Boosting

      • Shaowu Peng, Liang Lin, Jake Porway, Nong Sang, Song-Chun Zhu
      Pages 198-212

    5. Bayesian Inference for Layer Representation with Mixed Markov Random Field

      • Ru-Xin Gao, Tian-Fu Wu, Song-Chun Zhu, Nong Sang
      Pages 213-224

  5. Image Processing

    1. Dichromatic Reflection Separation from a Single Image

      • Yun-Chung Chung, Shyang-Lih Chang, Shen Cherng, Sei-Wang Chen
      Pages 225-241

    2. Noise Removal and Restoration Using Voting-Based Analysis and Image Segmentation Based on Statistical Models

      • Jonghyun Park, Nguyen Trung Kien, Gueesang Lee
      Pages 242-252
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  1. Energy Minimization Methods in Computer Vision and Pattern Recognition

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About this book

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.

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