Accession Number : ADA188012
Title : Visual Integration and Detection of Discontinuities: The Key Role of Intensity Edges.
Descriptive Note : Memorandum rept.,
Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB
Personal Author(s) : Gamble, Ed ; Poggio, Tomaso
PDF Url : ADA188012
Report Date : Oct 1987
Pagination or Media Count : 34
Abstract : Integration of several vision modules is likely to be one of the keys to the power and robustness of the human visual system. The problem of integrating early vision cues is also emerging as a central problem in current computer vision research. This paper suggests that integration is best performed at the location of discontinuities in early processes, such as discontinuities in image brightness, depth, motion, texture and color. Coupled Markov Random Field models, based on Bayes estimation techniques, can be used to combine vision modalities with their discontinuities. These models generate algorithms that map naturally onto parallel fine-grained architectures such as the Connection Machine. Derived a scheme to integrate intensity edges with stereo depth and motion field information and show results on synthetic and natural images. The use of intensity edges to integrate other visual cues and to help discover discontinuities emerges as a general and powerful principle.
Descriptors : *VISUAL PERCEPTION, *ARTIFICIAL INTELLIGENCE, *ROBOTICS, ALGORITHMS, BAYES THEOREM, BRIGHTNESS, COMPUTERS, CUES(STIMULI), DEPTH, DETECTION, DISCONTINUITIES, EDGES, ESTIMATES, HUMANS, IMAGES, INTEGRATION, INTENSITY, MOTION, VISION, MARKOV PROCESSES
Subject Categories : Biology
Distribution Statement : APPROVED FOR PUBLIC RELEASE