Boyer / Sarkar Perceptual Organization for Artificial Vision Systems

Erscheinungsjahr 2012
ISBN: 978-1-4615-4413-5
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 546, 349 Seiten, eBook

Reihe: The Springer International Series in Engineering and Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Boyer, Kim L.

Sarkar, Sudeep

Inhaltsverzeichnis

1 Perceptual Organization: Assessing the State of the Community and Charting New Research Directions.- I Focused Deliberations.- 2 Breakout Session Report: Principles and Methods.- 3 Breakout Session Report: Learning and Perceptual Organization.- 4 Breakout Session Report: Spatiotemporal Grouping.- II Discourses in Human and Machine Vision.- 5 Gestalt: from Phenomena to Laws.- 6 Perceptual Completion Behind Occluders: The Role of Convexity.- 7 Computational Implications of Biological Vision: A Gestalt Model of Spatial Perception.- 8 What Makes Viewpoint Invariant Properties Perceptually Salient?: A Computational Perspective.- 9 Contour and Texture Analysis for Image Segmentation.- 10 Perceptual Organization for Generic Object Descriptions.- 11 Toward Richer Labels for Visual Structure.- 12 Tensor Voting.- 13 An Observation on Saliency.- 14 Closed Curves in the Analysis and Segmentation of Images.- 15 The Curve Indicator Random Field: Curve Organization Via Edge Correlation.- 16 Euler Spiral for Shape Completion.- 17 Bayesian Extraction of Collinear Segment Chains from Digital Images.- 18 Object Detection by a Multiprimitive Preattentive Approach of the Perceptual Organization.