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Proceedings Paper

Motion estimation through efficient matching of a reduced number of reliable singular points
Author(s): Carlos R. del-Blanco; Fernando Jaureguizar; Luis Salgado; Narciso García
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Paper Abstract

Motion estimation in video sequences is a classical intensive computational task that is required for a wide range of applications. Many different methods have been proposed to reduce the computational complexity, but the achieved reduction is not enough to allow real time operation in a non-specialized hardware. In this paper an efficient selection of singular points for fast matching between consecutive images is presented, which allows to achieve real time operation. The selection of singular points lies in finding the image points that are robust to the noise and the aperture problem. This is accomplished by imposing restrictions related to the gradient magnitude and the cornerness. The neighborhood of each singular point is characterized by a complex descriptor vector, which presents a high robustness to illumination changes and small variations in the 3D camera viewpoint. The matching between singular points of consecutive images is performed by maximizing a similarity measure based on the previous descriptor vector. The set of correspondences yields a sparse motion vector field that accurately outlines the image motion. In order to demonstrate the efficiency of this approach, a video stabilization application has been developed, which uses the sparse motion vector field as input. Excellent results have been efficiency of the proposed motion estimation technique.

Paper Details

Date Published: 26 February 2008
PDF: 12 pages
Proc. SPIE 6811, Real-Time Image Processing 2008, 68110N (26 February 2008); doi: 10.1117/12.768125
Show Author Affiliations
Carlos R. del-Blanco, Univ. Politécnica de Madrid (Spain)
Fernando Jaureguizar, Univ. Politécnica de Madrid (Spain)
Luis Salgado, Univ. Politécnica de Madrid (Spain)
Narciso García, Univ. Politécnica de Madrid (Spain)

Published in SPIE Proceedings Vol. 6811:
Real-Time Image Processing 2008
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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