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Proceedings Paper

Multiple-frame motion estimation using simple region features
Author(s): Ronald D. Chaney
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Paper Abstract

Simple region features consist of the salient parts of regions bounded by the zero-crossings of the Laplacian of Gaussian operator. Simple region features have two fundamental advantages over existing features, such as edges. First, there is no threshold involved in simple region feature extraction process; thus, the process is not sensitive to the specification of the threshold. Second, the features consist of regions, rather than points. Consequently, they have geometric attributes, such as area, shape, and orientation, that can be exploited by subsequent processes. In this paper, we use simple region features to estimate camera motion and depth over multiple frames. A tracking algorithm computes the correspondence of the features across the image sequence; recursive estimates are obtained for the optical flow of each of the features. The geometric properties of the features are used to determine a measure of the reliability of the correspondence mapping. A weighted least-squares error estimate is obtained for the camera motion and the depth of each feature; the weights for each error term are derived from the reliability measure of the correspondence mappings.

Paper Details

Date Published: 13 October 1994
PDF: 16 pages
Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); doi: 10.1117/12.189083
Show Author Affiliations
Ronald D. Chaney, MIT AI Lab. (United States)

Published in SPIE Proceedings Vol. 2354:
Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision
David P. Casasent, Editor(s)

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