rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Energy Minimization Methods in Computer Vision and Pattern Recognition
    sub title: 6th International Conference, EMMCVPR 2007, Ezhou, China, August 27-29, 2007. Proceedings
  name:
    name part: Yuille, Alan L.
    role:
      role term: editor.
  name:
    name part: Zhu, Song-Chun.
    role:
      role term: editor.
  name:
    name part: Cremers, Daniel.
    role:
      role term: editor.
  name:
    name part: Wang, Yongtian.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 500 p. online resource.
  abstract: 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.
  table of contents: 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…
  note: edited by Alan L. Yuille, Song-Chun Zhu, Daniel Cremers, Yongtian Wang.
  subject:
    topic: Computer science
  subject:
    topic: Algorithms
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer graphics
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Pattern Recognition
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Computer Graphics
  subject:
    topic: Algorithm Analysis and Problem Complexity
  subject:
    topic: Data Mining and Knowledge Discovery
  classification: TA1637-1638
  classification: TA1634
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 4679
  identifier: 9783540741985
  identifier: http://dx.doi.org/10.1007/978-3-540-74198-5
  record info:
    record creation date: 100301
    record change date: 20151204180452.0
    record identifier: 978-3-540-74198-5