Use of an Evaluation and Diagnosis Method to Improve Tracking
Performances

LES AUTEURS Benoit Georis, Francois Bremond, Monique Thonnat and Benoit Macq

RESUME:

This paper presents a general framework for analyzing the evaluation of a tracking algorithm in order to improve it. We first propose a classification of the various errors encountered during the motion
detection and the tracking process. This classification is done using a comparison between tracking outputs and ground truth. We propose two evaluation algorithms, a global one and a more precise one. Second, we show how to use this classification to diagnose the tracking errors and to find relevant parameters to solve each problem type and to determine criteria to tune these parameters with respect to the scene environment. This technique is applied to the tracker module of a video interpretation platform whose main goal is to recognize human behaviours. Results are presented for several video sequences taken from a static calibrated camera in three different contexts: a bank agency, a metro platform and an office.

Mots clé: human tracking, performance assessment, supervised evaluation

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BibTeX reference:

@INPROCEEDINGS{Georis03,
 AUTHOR = {B. Georis and F. Bremond and M. Thonnat and B. Macq},
 BOOKTITLE = {Proceedings of VIIP'03- 3rd IASTED International Conference 
 on Visualization, Imaging and Image Proceeding},
 TITLE = {Use of an Evaluation and Diagnosis Method to Improve Tracking Performances},
 MONTH = {SEP 8-10},
 YEAR = {2003},
}

Dernière mise à jour : 14/08/03
Catherine.Martin@sophia.inria.fr