Perceptual Organization for Artificial Vision Systems / Edition 1

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Perceptual Organization for Artificial Vision Systems includes contrib utions by the world's leading researchers in the field. It explores ne w models, theories, and algorithms for perceptual organization, as wel l as demonstrates the means for bringing research results and theoreti cal principles to fruition in the construction of computer vision syst ems. The focus of this collection is on the design of artificial visio n systems. The chapters comprise contributions from researchers in bot h computer vision and human vision.

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Table of Contents

Contributing Authors. 1. Introduction; K.L. Boyer, S. Sarkar. Part I: Focused Deliberations. 2. Principles and Methods; D. Jacobs, et al. 3. Learning and Perceptual Organization; E. Saund, et al. 4. Spatiotemporal Grouping; K.L. Boyer, et al. Part II: Discourses in Human and Machine Vision. 5. Gestalt: From Phenomena to Laws; M. Kubovy, S. Gepshtein. 6. Convexity in Perceptual Completion; Z. Liu, et al. 7. A Gestalt Model of Spatial Perception; S. Lehar. 8. What Makes Viewpoint Invariant Properties Perceptually Salient? D. Jacobs. 9. Contour and Texture Analysis for Image Segmentation; J. Malik, et al. 10. Perceptual Organization for Generic Object Description; R. Nevatia. 11. Toward Richer Labels for Visual Structure; E. Saund. 12. Tensor Voting; C.-K. Tang, et al. 13. An observation on saliency; M. Lindenbaum, A. Berengolts. 14. Closed Curves in the Analysis and Segmentation of Images; K.K. Thornberg, L.R. Williams. 15. The curve indicator random field: Curve organization via edge correlation; J. August, S.W. Zucker. 16. Euler Spiral for Shape Completion; B.B. Kimia, et al. 17. Bayesian Extraction of Collinear Segment Chains from Digital Images; D. Crevier. 18. Object Detection by Multiprimitive Preattentive Perceptual Organization; P. Vasseur, et al. Index.

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