Author： Xiong Y. Shafer S.A.
Publisher： Academic Press
ISSN： 1077-3142
Source： Computer Vision and Image Understanding, Vol.69, Iss.2, 1998-02, pp. : 222-245
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Abstract
This paper presents a structure-from-motion system which delivers dense structure information from a sequence of dense optical flows. Most traditional feature-based approaches cannot be extended to compute dense structure due to impractical computational complexity. We demonstrate that by decomposing uncertainty information into independent and correlated parts and employing an eigen-based uncertainty representation, we can decrease these complexities from O(N2) to O(N) for every frame, where N is the number of pixels in the images. We also show that our new representation of structural information makes it easy to merge over a long image sequence even when no specific feature is tracked over multiple frames. Copyright 1998 Academic Press.
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