Biologically Motivated Computer Vision

1. Invited Paper (5)

   1. Active Vision from Multiple Cues

      • Henrik Christensen, Jan-Olof Eklundh

      Pages 209-216

2. Posters

   1. An Efficient Data Structure for Feature Extraction in a Foveated Environment

      • Efri Nattel, Yehezkel Yeshurun

      Pages 217-226

   2. Parallel Trellis Based Stereo Matching Using Constraints

      • Hong Jeong, Yuns Oh

      Pages 227-237

   3. Unsupervised Learning of Biologically Plausible Object Recognition Strategies

      • Bruce A. Draper, Kyungim Baek

      Pages 238-247

   4. Structured Kalman Filter for Tracking Partially Occluded Moving Objects

      • Dae-Sik Jang, Seok-Woo Jang, Hyung-Il Choi

      Pages 248-257

   5. Face Recognition under Varying Views

      • A. Sehad, H. Hocini, A. Hadid, M. Djeddi, S. Ameur

      Pages 258-267

   6. Time Delay Effects on Dynamic Patterns in a Coupled Neural Model

      • Seon Hee Park, Seunghwan Kim, Hyeon-Bong Pyo, Sooyeul Lee, Sang-Kyung Lee

      Pages 268-275

   7. Pose-Independent Object Representation by 2-D Views

      • Jan Wieghardt, Christoph von der Malsburg

      Pages 276-285

   8. An Image Enhancement Technique Based on Wavelets

      • Hae-Sung Lee, Yongbum Cho, Hyeran Byun, Jisang Yoo

      Pages 286-296

   9. Front-End Vision: A Multiscale Geometry Engine

      • Bart M. ter Haar Romeny, Luc M. J. Florack

      Pages 297-307

   10. Face Reconstruction Using a Small Set of Feature Points

       • Bon-Woo Hwang, Volker Blanz, Thomas Vetter, Seong-Whan Lee

       Pages 308-315

   11. Modeling Character Superiority Effect in Korean Characters by Using IAM

       • Chang Su Park, Sung Yang Bang

       Pages 316-325

   12. Wavelet-Based Stereo Vision

       • Minbo Shim

       Pages 326-335

   13. A Neural Network Model for Long-Range Contour Diffusion by Visual Cortex

       • Stéphane Fischer, Birgitta Dresp, Charles Kopp

       Pages 336-342

   14. Automatic Generation of Photo-Realistic Mosaic Image

       • Jong-Seung Park, Duk-Ho Chang, Sang-Gyu Park

       Pages 343-352

   15. The Effect of Color Differences on the Detection of the Target in Visual Search

       • Ji-Young Hong, Kyung-Ja Cho, Kwang-Hee Han

       Pages 353-358

   16. A Color-Triangle-Based Approach to the Detection of Human Face

       • Chiunhsiun Lin, Kuo-Chin Fan

       Pages 359-368

   17. Multiple People Tracking Using an Appearance Model Based on Temporal Color

       • Hyung-Ki Roh, Seong-Whan Lee

       Pages 369-378

   18. Face and Facial Landmarks Location Based on Log-Polar Mapping

       • Sung-Il Chien, Il Choi

       Pages 379-386

   19. Biology-Inspired Early Vision System for a Spike Processing Neurocomputer

       • Jörg Thiem, Carsten Wolff, Georg Hartmann

       Pages 387-396

It is our great pleasure and honor to organize the First IEEE Computer Society International Workshop on Biologically Motivated Computer Vision (BMCV 2000). The workshop BMCV 2000 aims to facilitate debates on biologically motivated vision systems and to provide an opportunity for researchers in the area of vision to see and share the latest developments in state-of-the-art technology. The rapid progress being made in the field of computer vision has had a tremendous impact on the modeling and implementation of biologically motivated computer vision. A multitude of new advances and findings in the domain of computer vision will be presented at this workshop. By December 1999 a total of 90 full papers had been submitted from 28 countries. To ensure the high quality of workshop and proceedings, the program committee selected and accepted 56 of them after a thorough review process. Of these papers 25 will be presented in 5 oral sessions and 31 in a poster session. The papers span a variety of topics in computer vision from computational theories to their implementation. In addition to these excellent presentations, there will be eight invited lectures by distinguished scientists on “hot” topics. We must add that the program committee and the reviewers did an excellent job within a tight schedule.

• Biologically Motivated Computing
• Bionformatics
• Computer Vision
• Image Processing
• Newral Networks
• Object Recognition
• Pattern Recognition
• cognition
• neural network
• algorithm analysis and problem complexity

• Center for Artificial Vision Research, Korea University, Seoul, Korea

  Seong-Whan Lee

• Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany

  Heinrich H. Bülthoff

• Department of Brain and Cognitive Sciences Artificial Intelligence Laboratory, E25-218, Massachusetts Institute of Technology, Cambridge, USA

  Tomaso Poggio

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