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UnBiased Linear Algorithm for Recovering ThreeDimensional Motion from optical Flow
Norio TAGAWA Takashi TORIU Toshio ENDOH
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E76D
No.10
pp.12631275 Publication Date: 1993/10/25
Online ISSN:
DOI:
Print ISSN: 09168532 Type of Manuscript: PAPER Category: Image Processing, Computer Graphics and Pattern Recognition Keyword: image processing, computer vision, motion analysis, structure from motion, optical flow,
Full Text: PDF(954.6KB) >>Buy this Article
Summary:
This paper describes a noise resistant algorithm for recovering the threedimensional motion of a rigid object from optical flow. First, it is shown that in the absence of noise threedemensional motion can be obtained exactly by a linear algorithm except in the special case in which the surface of the object is on a general quadratic surface passing through the viewpoint, and the normal vector of the surface at the viewpoint is perpendicular to the translation velocity vector. In the presence of noise, an evaluation function is introduced based on the least squares method. It is shown, however, that the solution which minimizes the evaluation function is not always optimal due to statistical bias. To deal with this problem, a method to eliminate the statistical bias in the evaluation function is proposed for zero mean white noise. Once the statistical bias is eliminated, the solution of the linear algorithm coincides with the correct solution by means of expectation. In this linear algorithm, only the eigenvector corresponding to the zero eigenvalue of a 33 matrix is necessary to find the translational velocity. Once the translational velocity is obtained, the rotational velocity can be computed directly. This method is also shown to be noise resistant by computer simulation.

