Perceptual Organization for Artificial Vision Systems

1. Front Matter

   Pages i-xiii

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2. Introduction

   1. Perceptual Organization: Assessing the State of the Community and Charting New Research Directions

      • Kim L. Boyer, Sudeep Sarkar

      Pages 1-13

3. Focused Deliberations

   1. Front Matter

      Pages 15-15

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   2. Breakout Session Report: Principles and Methods

      • David Jacobs, Jitendra Malik, Ram Nevatia

      Pages 17-28

   3. Breakout Session Report: Learning and Perceptual Organization

      • Eric Saund, Jonas August, Joachim Buhmann, Daniel Crevier, Greet Frederix, Danny Roobaert

      Pages 29-32

   4. Breakout Session Report: Spatiotemporal Grouping

      • Kim L. Boyer, Daniel Fagerström, Michael Kubovy, Peter Johansen, Sudeep Sarkar

      Pages 33-38

4. Discourses in Human and Machine Vision

   1. Front Matter

      Pages 39-39

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   2. Gestalt: From Phenomena to Laws

      • Michael Kubovy, Sergei Gepshtein

      Pages 41-71

   3. Perceptual Completion Behind Occluders: The Role of Convexity

      • Zili Liu, David W. Jacobs, Ronen Basri

      Pages 73-90

   4. Computational Implications of Biological Vision: A Gestalt Model of Spatial Perception

      • Steven Lehar

      Pages 91-119

   5. What Makes Viewpoint Invariant Properties Perceptually Salient?: A Computational Perspective

      • David Jacobs

      Pages 121-138

   6. Contour and Texture Analysis for Image Segmentation

      • Jitendra Malik, Serge Belongie, Thomas Leung, Jianbo Shi

      Pages 139-172

   7. Perceptual Organization for Generic Object Descriptions

      • R. Nevatia

      Pages 173-189

   8. Toward Richer Labels for Visual Structure

      • Eric Saund

      Pages 191-214

   9. Tensor Voting

      • Chi-Keung Tang, Mi-Suen Lee, Gérard Medioni

      Pages 215-237

   10. An Observation on Saliency

       • Michael Lindenbaum, Alexander Berengolts

       Pages 239-248

   11. Closed Curves in the Analysis and Segmentation of Images

       • K. K. Thornber, L. R. Williams

       Pages 249-263

   12. The Curve Indicator Random Field: Curve Organization Via Edge Correlation

       • Jonas August, Steven W. Zucker

       Pages 265-288

   13. Euler Spiral for Shape Completion

       • Benjamin B. Kimia, Ilana Frankel, Ana-Maria Popescu

       Pages 289-309

   14. Bayesian Extraction of Collinear Segment Chains from Digital Images

       • Daniel Crevier

       Pages 311-323

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September 1999. The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.'
Perceptual organization can be defined as the ability to impose structural regularity on sensory data, so as to group sensory primitives arising from a common underlying cause. This book explores new models, theories, and algorithms for perceptual organization.
Perceptual Organization for Artificial Vision Systems includes contributions by the world's leading researchers in the field. It explores new models, theories, and algorithms for perceptual organization, as well as demonstrates the means for bringing research results and theoretical principles to fruition in the construction of computer vision systems. The focus of this collection is on the design of artificial vision systems. The chapters comprise contributions from researchers in both computer vision and human vision.

• Image segmentation
• Textur
• algorithms
• computer vision
• machine vision

• The Ohio State University, Columbus, USA

  Kim L. Boyer

• University of South Florida, Tampa, USA

  Sudeep Sarkar

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