3-D Motion Estimation from Optical Flow with Low Computational Cost and Small Variance

Norio TAGAWA  Takashi TORIU  Toshio ENDOH  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E79-D   No.3   pp.230-241
Publication Date: 1996/03/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing,Computer Graphics and Pattern Recognition
Keyword: 
computer vision,  3-D motion analysis,  optical flow,  unbiased estimator,  maximum likelihood estimator,  

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Summary: 
In this paper, we study three-dimensional motion estimation using optical flow. We construct a weighted quotient-form objective function that provides an unbiased estimator. Using this objective function with a certain projection operator as a weight drastically reduces the computational cost for estimation compared with using the maximum likelihood estimator. To reduce the variance of the estimator, we examine the weight, and we show by theoretical evaluations and simulations that, with an appropriate projection function, and when the noise variance is not too small, this objective function provides an estimator whose variance is smaller than that of the maximum likelihood estimator. The use of this projection is based on the knowledge that the depth function has a positive value (i. e., the object is in front of the camera) and that it is generally smooth.