NDLI: An integrated Bayesian approach to layer extraction from image sequences

Content Provider	IEEE Xplore Digital Library
Author	Torr, P.H.S. Szeliski, R. Anandan, P.
Copyright Year	1979
Abstract	This paper describes a Bayesian approach for modeling 3D scenes as collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. In contrast to much of the previous work on layer-based motion modeling, which computes layered descriptions of 2D image motion, our work leads to a 3D description of the scene. There are two contributions within the paper. The first is to formulate the prior assumptions about the layers and scene within a Bayesian decision making framework which is used to automatically determine the number of layers and the assignment of individual pixels to layers. The second is algorithmic. In order to achieve the optimization, a Bayesian version of RANSAC is developed with which to initialize the segmentation. Then, a generalized expectation maximization method is used to find the MAP solution.
Sponsorship	IEEE Computer Society
Starting Page	297
Ending Page	303
Page Count	7
File Size	705744
File Format	PDF
ISSN	01628828
Volume Number	23
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Image sequences Layout Image segmentation Solid modeling Computer vision Sprites (computer) Decision making Stereo vision Motion estimation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software

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