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Authors: Yassine Benabbas ; Samir Amir ; Adel Lablack and Chabane Djeraba

Affiliation: University of Lille1, TELECOM Lille1 and IRCICA, France

Keyword(s): Human action recognition, Motion analysis, Video understanding.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Human-Computer Interaction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Signal Processing, Sensors, Systems Modeling and Control ; Software Engineering ; Video Analysis

Abstract: This paper proposes an approach that uses direction and magnitude models to perform human action recognition from videos captured using monocular cameras. A mixture distribution is computed over the motion orientations and magnitudes of optical flow vectors at each spatial location of the video sequence. This mixture is estimated using an online k-means clustering algorithm. Thus, a sequence model which is composed of a direction model and a magnitude model is created by circular and non-circular clustering. Human actions are recognized via a metric based on the Bhattacharyya distance that compares the model of a query sequence with the models created from the training sequences. The proposed approach is validated using two public datasets in both indoor and outdoor environments with low and high resolution videos.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Benabbas, Y.; Amir, S.; Lablack, A. and Djeraba, C. (2011). HUMAN ACTION RECOGNITION USING DIRECTION AND MAGNITUDE MODELS OF MOTION. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP; ISBN 978-989-8425-47-8; ISSN 2184-4321, SciTePress, pages 277-285. DOI: 10.5220/0003323702770285

@conference{visapp11,
author={Yassine Benabbas. and Samir Amir. and Adel Lablack. and Chabane Djeraba.},
title={HUMAN ACTION RECOGNITION USING DIRECTION AND MAGNITUDE MODELS OF MOTION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP},
year={2011},
pages={277-285},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003323702770285},
isbn={978-989-8425-47-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP
TI - HUMAN ACTION RECOGNITION USING DIRECTION AND MAGNITUDE MODELS OF MOTION
SN - 978-989-8425-47-8
IS - 2184-4321
AU - Benabbas, Y.
AU - Amir, S.
AU - Lablack, A.
AU - Djeraba, C.
PY - 2011
SP - 277
EP - 285
DO - 10.5220/0003323702770285
PB - SciTePress