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Estimation of 3-D Motion from Optical Flow with Unbiased Objective Function
Norio TAGAWA Takashi TORIU Toshio ENDOH
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1994/10/25
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing, Computer Graphics and Pattern Recognition
computer vision, 3-D motion analysis, optical flow, statistical bias, unbiased estimator,
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This paper describes a noise resistant algorithm for estimating 3-D rigid motion from optical flow. We first discuss the problem of constructing the objective function to be minimized. If a Gaussian distribution is assumed for the niose, it is well-known that the least-squares minimization becomes the maximum likelihood estimation. However, the use of this objective function makes the minimization procedure more expensive because the program has to go through all the points in the image at each iteration. We therefore introduce an objective function that provides unbiased estimators. Using this function reduces computational costs. Furthermore, since good approximations can be analytically obtained for the function, using them as an initial guess we can apply an iterative minimization method to the function, which is expected to be stable. The effectiveness of this method is demonstrated by computer simulation.