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Reducing “Structure from Motion”: a general framework for dynamic vision. 1. Modeling

Soatto, Stefano and Perona, Pietro (1998) Reducing “Structure from Motion”: a general framework for dynamic vision. 1. Modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20 (9). pp. 933-942. ISSN 0162-8828. http://resolver.caltech.edu/CaltechAUTHORS:SOAieeetpami98a

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Abstract

The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of apparently unrelated models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction. The “natural” dynamic model, derived from the rigidity constraint and the projection model, is first reduced by explicitly decoupling structure (depth) from motion. Then, implicit decoupling techniques are explored, which consist of imposing that some function of the unknown parameters is held constant. By appropriately choosing such a function, not only can we account for models seen so far in the literature, but we can also derive novel ones.


Item Type:Article
Additional Information:© Copyright 1998 IEEE. Reprinted with permission. Manuscript received 18 Dec. 1995; revised 2 July 1998. Recommended for acceptance by D.J. Kriegman.
Subject Keywords:Visual motion estimation, epipolar geometry, motion decoupling, compensation, fixation, parallax, output stabilization, model reduction
Record Number:CaltechAUTHORS:SOAieeetpami98a
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:SOAieeetpami98a
Alternative URL:http://dx.doi.org/10.1109/34.713360
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:6501
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:11 Dec 2006
Last Modified:26 Dec 2012 09:21

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