Second International Workshop on

Statistical and Computational Theories of Vision

-- Modeling, Learning, Computing, and Sampling

Vancouver, Canada, July 13, 2001.

Scope, Program Committee, and contact information

Link to the 1st Int'l Workshop on STCV 1999.

The proceedings of the workshop are published on this web page. All papers should be treated as regular publication and be referenced as
Proc. of IEEE workshop on Statistical and Computational Theories of Vision, Vancouver, CA, July 2001.

Proceedings of the Workshop

[ The meeting schedule (.ps) ]

Session 1. Statistics of Natural Imagery and Visual Learning:

  • The Complex statistics of high contrast patches in natural images,
    A. Lee, K. Pedersen, D. Mumford (ps.gz)
  • Sparse Coding in Practice
    C. Chennbhotla and A. Jepson (ps.gz)
  • Template Learning from Atomic Representations: A Wavelet Based Approach to Pattern Analysis
    C. Scott and R. Nowak (pdf)

    Session 2. Effective Computing and Sampling

  • Bethe free energy, Kikuchi approximations, and belief propagation algorithms
    J. Yedidia, W. T. Freeman, and Y. Weiss (pdf)
  • A Double-Loop Algorithm to Minimize the Bethe and Kikuchi Free Energies
    Alan L. Yuille (ps)
  • Asymptotically Admissible Texture Synthesis
    Y.Q. Xu, S.C. Zhu, B.N. guo, and H.Y. Shum (pdf)
  • Efficient Computation of Kernel Density Estimation using Fast Gauss Transform with Applications for segmentation and tracking
    A. Elgammal, R. Duraiswami, L. S. Davis

    Session 3. Face and Material Recognition with Fast algorithms

  • Robust Real Time Object Detection
    P. Viola and M. Jones (ps.gz)
  • Surface reflectance Estimation and natural illumination statistics
    R. Dror, T. Adelson, A. Willsky (pdf)
  • Constructing structures of facial identities on the view sphere using kernel discriminant analysis
    Y. M. Li, S. G. Gong, H. Liddell (pdf)

    Session 4. Random field theories

  • A generative model for image contours: a completely characterized non-Gaussian joint distribution
    J. August and S. W. Zucker (pdf)
  • G-factors: Relating Distributions on Features to Distributions on Images
    J. M. Coughlan and A. L. Yuille (pdf)
  • From Markov Random Fields to Associative Memories and Back: Spin Glass Markov Random Fields
    B. Caputo, and H. Niemann (ps.gz)

    Session 5 Panel Discussion (?)