Soatto, Stefano and Perona, Pietro (1996) Reducing “Structure From Motion”. In: 1996 IEEE computer society conference on computer vision and pattern recognition: proceedings. IEEE Computer Society Press , Los Alamitos, CA, pp. 825-832. ISBN 0-8186-7258-7 http://resolver.caltech.edu/CaltechAUTHORS:20120209-100001725
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The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of different 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 by the rigidity constraint and the perspective projection, 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 all models seen so far in the literature, but we can also derive novel ones. Casting all the different models in a common framework allows us to compare their geometric properties on common experimental grounds.
|Item Type:||Book Section|
|Additional Information:||© 1996 IEEE. Date of Current Version: 06 August 2002. Research sponsored by NSF NYI Award, NSF ERC in Neuromorphic Systems Engineering, ONR grant N00014-93-1-0990.|
|Official Citation:||Soatto, S.; Perona, P.; , "Reducing “structure from motion”," Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on , vol., no., pp.825-832, 18-20 Jun 1996 doi: 10.1109/CVPR.1996.517167 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=517167&isnumber=11029|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Ruth Sustaita|
|Deposited On:||09 Feb 2012 18:25|
|Last Modified:||23 Aug 2016 10:09|
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