Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

David Marimon; Yousri Abdeljaoued; Bruno Palacios; Touradj Ebrahimi

doi:10.1117/12.702800

29 January 2007 Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

David Marimon, Yousri Abdeljaoued, Bruno Palacios, Touradj Ebrahimi

Author Affiliations +

Proceedings Volume 6508, Visual Communications and Image Processing 2007; 650808 (2007) https://doi.org/10.1117/12.702800
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solved by an assignment algorithm. A track management method is also developed. In particular a track continuation method and a track quality indicator are presented. The evaluation of the tracking system on real sequences shows that the IMM filter combined with the assignment algorithm outperforms the Kalman filter, used with the Nearest Neighbour (NN) filter, in terms of data association performance and robustness to sudden feature point manoeuvre.

Citation Download Citation

David Marimon, Yousri Abdeljaoued, Bruno Palacios, and Touradj Ebrahimi "Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm", Proc. SPIE 6508, Visual Communications and Image Processing 2007, 650808 (29 January 2007); https://doi.org/10.1117/12.702800

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