Biologically Motivated Computer Vision

1. Front Matter

   Pages I-XIV

   PDF

2. Invited Paper (1)

   1. CBF: A New Framework for Object Categorization in Cortex

      • Maximilian Riesenhuber, Tomaso Poggio

      Pages 1-10

3. Invited Paper (2)

   1. The Perception of Spatial Layout in a Virtual World

      • Heinrich H. Bülthoff, Chris G. Christou

      Pages 10-19

4. Segmentation, Detection and Object Recognition

   1. Towards a Computational Model for Object Recognition in IT Cortex

      • David G. Lowe

      Pages 20-31

   2. Straight Line Detection as an Optimization Problem: An Approach Motivated by the Jumping Spider Visual System

      • Felipe Miney G. da Costa, Luciano da F. Costa

      Pages 32-41

   3. Factorial Code Representation of Faces for Recognition

      • Seungjin Choi, Oyoung Lee

      Pages 42-51

   4. Distinctive Features Should Be Learned

      • Justus H. Piater, Roderic A. Grupen

      Pages 52-61

   5. Moving Object Segmentation Based on Human Visual Sensitivity

      • Kuk-Jin Yoon, In-So Kweon, Chang-Yeong Kim, Yang-Seok Seo

      Pages 62-72

5. Invited Paper (3)

   1. Object Classification Using a Fragment-Based Representation

      • Shimon Ullman, Erez Sali

      Pages 73-87

6. Computational Model

   1. Confrontation of Retinal Adaptation Model with Key Features of Psychophysical Gain Behavior Dynamics

      • Eilon Sherman, Hedva Spitzer

      Pages 88-97

   2. Polarization-Based Orientation in a Natural Environment

      • Volker Müller

      Pages 98-107

   3. Computation Model of Eye Movement in Reading Using Foveated Vision

      • Yukio Ishihara, Satoru Morita

      Pages 108-117

   4. New Eyes for Shape and Motion Estimation

      • Patrick Baker, Robert Pless, Cornelia Fermüller, Yiannis Aloimonos

      Pages 118-128

   5. Top-Down Attention Control at Feature Space for Robust Pattern Recognition

      • Su-In Lee, Soo-Young Lee

      Pages 129-138

   6. A Model for Visual Camouflage Breaking

      • Ariel Tankus, Yehezkel Yeshurun

      Pages 139-149

7. Active and Attentive Vision

   1. Development of a Biologically Inspired Real-Time Visual Attention System

      • Olivier Stasse, Yasuo Kuniyoshi, Gordon Cheng

      Pages 150-159

   2. Real-Time Visual Tracking Insensitive to Three-Dimensional Rotation of Objects

      • Young-Joo Cho, Bum-Jae You, Joonhong Lim, Sang-Rok Oh

      Pages 160-167

   3. Heading Perception and Moving Objects

      • Nam-Gyoon Kim

      Pages 168-178

   4. Dynamic Vergence Using Disparity Flux

      • Hee-Jeong Kim, Myung-Hyun Yoo, Seong-Whan Lee

      Pages 179-188

8. Invited Paper (4)

   1. Computing in Cortical Columns: curve inference and stereo correspondence

      • Steven W. Zucker

      Pages 189-208

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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