DocumentCode :
1425882
Title :
Reducing “Structure from Motion”: a general framework for dynamic vision. 1. Modeling
Author :
Soatto, Stefano ; Perona, Pietro
Author_Institution :
Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA
Volume :
20
Issue :
9
fYear :
1998
fDate :
9/1/1998 12:00:00 AM
Firstpage :
933
Lastpage :
942
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
Keywords :
image reconstruction; image sequences; motion estimation; recursive estimation; decoupling techniques; dynamic vision; dynamical system reduction; estimation techniques; modeling; monocular image sequences; projection model; recursive estimation; rigidity constraint; structure-from-motion recovery; Cameras; Geometry; Image analysis; Image reconstruction; Image sequences; Image storage; Layout; Motion estimation; Recursive estimation; Reduced order systems;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.713360
Filename :
713360
Link To Document :
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