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Parametric Estimation of Optical Flow from Two Perspective Views

Norio TAGAWA, Atsuya INAGAKI, Akihiro MINAGAWA

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Summary :

Since the detection of optical flow (two-dimensional motion field on an image) from image sequences is essentially an ill-posed problem, most of the conventional methods use a smoothness constraint for optical flow heuristically and detect reasonable optical flow. However, little discussion exists regarding the degree of smoothness. Furthermore, to recover the relative three-dimensional motion and depth between a camera and a rigid object, in general at first, the optical flow is detected without a rigid motion constraint, and next, the motion and depth are estimated using the detected optical flow. Rigorously speaking, the optical flow should be detected with such a constraint, and consequently three-dimensional motion and depth should be determined. To solve these problems, in this paper, we apply a parametric model to an optical flow, and construct an estimation algorithm based on this model.

Publication
IEICE TRANSACTIONS on Information Vol.E84-D No.4 pp.485-494
Publication Date
2001/04/01
Publicized
Online ISSN
DOI
Type of Manuscript
PAPER
Category
Image Processing, Image Pattern Recognition

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