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: Statistical Methods in Video Processing
    sub title: ECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers
  name:
    name part: Comaniciu, Dorin.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Kanatani, Kenichi.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Mester, Rudolf.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Suter, David.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2004
    edition: 1st ed. 2004.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VIII, 200 p. online resource.
  abstract: The 2nd International Workshop on Statistical Methods in Video Processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on Computer Vision. A total of 30 papers were submitted to the workshop. Of these, 17 papers were accepted for presentation and included in these proceedings, following a double-blind review process. The workshop had 42 registered participants. The focus of the meeting was on recent progress in the application of - vanced statistical methods to solve computer vision tasks. The one-day scienti?c program covered areas of high interest in vision research, such as dense rec- struction of 3D scenes, multibody motion segmentation, 3D shape inference, errors-in-variables estimation, probabilistic tracking, information fusion, optical ?owcomputation,learningfornonstationaryvideodata,noveltydetectionin- namic backgrounds, background modeling, grouping using feature uncertainty, and crowd segmentation from video. We wish to thank the authors of all submitted papers for their interest in the workshop.Wealsowishtothankthemembersofourprogramcommitteeandthe external reviewers for their commitment of time and e?ort in providing valuable recommendations for each submission. We are thankful to Vaclav Hlavac, the General Chair of ECCV 2004, and to Radim Sara, for the local organization of the workshop and registration management. We hope you will ?nd these proceedings both inspiring and of high scienti?c quality.
  table of contents: 3D Geometry -- Towards Complete Free-Form Reconstruction of Complex 3D Scenes from an Unordered Set of Uncalibrated Images -- Geometric Structure of Degeneracy for Multi-body Motion Segmentation -- Virtual Visual Hulls: Example-Based 3D Shape Inference from Silhouettes -- Unbiased Errors-In-Variables Estimation Using Generalized Eigensystem Analysis -- Tracking -- Probabilistic Tracking of the Soccer Ball -- Multi-Model Component-Based Tracking Using Robust Information Fusion -- A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection -- Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion -- Combining Simple Models to Approximate Complex Dynamics -- Background Modeling -- Online Adaptive Gaussian Mixture Learning for Video Applications -- Novelty Detection in Image Sequences with Dynamic Background -- A Framework for Foreground Detection in Complex Environments -- A Background Maintenance Model in the Spatial-Range Domain -- Image/Video Analysis -- A New Robust Technique for Stabilizing Brightness Fluctuations in Image Sequences -- Factorization of Natural 4 × 4 Patch Distributions -- Parametric and Non-parametric Methods for Linear Extraction -- Crowd Segmentation Through Emergent Labeling.
  note: edited by Dorin Comaniciu, Kenichi Kanatani, Rudolf Mester, David Suter.
  subject:
    topic: Optical data processing
  subject:
    topic: Computer graphics
  subject:
    topic: Pattern recognition
  subject:
    topic: Mathematical statistics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Algorithms
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Computer Graphics
  subject:
    topic: Pattern Recognition
  subject:
    topic: Probability and Statistics in Computer Science
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Algorithm Analysis and Problem Complexity
  classification: TA1630-1650
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 3247
  identifier: 9783540302124
  identifier: https://doi.org/10.1007/b104157
  record info:
    record creation date: 121227
    record change date: 20191220130610.0
    record identifier: 978-3-540-30212-4