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Authors: Alexandre Hervieu 1 ; Patrick Bouthemy 1 and Jean-Pierre Le Cadre 2

Affiliations: 1 INRIA, Centre Rennes - Bretagne Atlantique, France ; 2 INRIA; CNRS, Campus Universitaire de Beaulieu, France

ISBN: 978-989-8111-21-0

Keyword(s): Image sequence analysis, Image motion analysis, Hidden Markov models, Pattern recognition.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: This paper describes an original statistical trajectory-based approach which can address several issues related to dynamic video content understanding: unsupervised clustering of events, recognition of events corresponding to learnt classes of dynamic video contents, and detection of unexpected events. Appropriate local differ- ential features combining curvature and motion magnitude are robustly computed on the trajectories. They are invariant to image translation, in-the-plane rotation and scale transformation. The temporal causality of these features is then captured by hidden Markov models whose states are properly quantized values, and similarity between trajectories is expressed by exploiting the HMM framework. We report experiments on two sets of data, a first one composed of typical classes of synthetic (noised) trajectories (such as parabola or clothoid), and a second one formed with trajectories computed in sports videos. We have also favorably compared our method to other ones, including feature histogram comparison, use of the longest common subsequence (LCSS) distance and SVM-based classification. (More)

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Paper citation in several formats:
Hervieu A.; Bouthemy P.; Le Cadre J. and (2008). VIDEO EVENT CLASSIFICATION AND DETECTION USING 2D TRAJECTORIES.In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 158-166. DOI: 10.5220/0001073001580166

@conference{visapp08,
author={Alexandre Hervieu and Patrick Bouthemy and Jean{-}Pierre {Le Cadre}},
title={VIDEO EVENT CLASSIFICATION AND DETECTION USING 2D TRAJECTORIES},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={158-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001073001580166},
isbn={978-989-8111-21-0},
}

TY - CONF

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - VIDEO EVENT CLASSIFICATION AND DETECTION USING 2D TRAJECTORIES
SN - 978-989-8111-21-0
AU - Hervieu, A.
AU - Bouthemy, P.
AU - Le Cadre, J.
PY - 2008
SP - 158
EP - 166
DO - 10.5220/0001073001580166

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