Analysis and Representation of Complex Scenes using Perceptual Organization
PhD. Thesis, University of Montpellier II, Nimes France
Technical Report 1997 (english)
Rapport Technique 1997 (francais)
Rapport Technique 1996 (francais)
Texte integral (francais)
Introduction (francais)
I. Perception de structures curvilignes en vision par ordinateur
I.1 Vision naturelle et artificielle (francais)
I.2 Analyse et interpretation des scenes de contours (francais)
I.3 Groupement perceptuel en vision par ordinateur (francais)
II. Analyse de scenes de contours par groupement perceptuel
II.1 Saillance structurelle et groupements elementaires (francais)
II.2 Elements de representation et groupements intermediaires (francais)
II.3 Groupements de haut niveau et mise en correspondance (francais)
Conclusion et Annexes (francais)
Bibliographie (francais)
Powerpoint Slides (francais)
Powerpoint Slides (english)
Abstract
A possible definition for Computer Vision is the automatic inference of decisions from pictures with the help of computers. In this context, extracting one or many representations from the image of a scene plays a fundamental role.
Human Vision shows the existence of numerous mechanisms, the purpose of which is to continuously guide perception through the constant low of visual information. At a psychological level, more difficult to express in computational terms, one possible contribution to Computer Vision comes from Perceptual Grouping.
The work described in this manuscript uses the perspective of perceptual grouping to structure images into significant visual elements. We propose a progressive approach to extract visually important features from the contours of an image and give useful elements of representation of the scene for a higher recognition process.
We finally show how these visual elements can be used for the detection and matching of junctions between two images. Various results on synthetic and real images confirm the relevance of our approach.