Fast Violence Detection in Video

Oscar Deniz, Ismael Serrano, Gloria Bueno, Tae-Kyun Kim

2014

Abstract

Whereas the action recognition problem has become a hot topic within computer vision, the detection of fights or in general aggressive behavior has been comparatively less studied. Such capability may be extremely useful in some video surveillance scenarios like in prisons, psychiatric centers or even in camera phones. Recent work has considered the well-known Bag-of-Words framework often used in generic action recognition for the specific problem of fight detection. Under this framework, spatio-temporal features are extracted from the video sequences and used for classification. Despite encouraging results in which near 90% accuracy rates were achieved, the computational cost of extracting such features is prohibitive for practical applications, particularly in surveillance and media rating systems. The task of violence detection may have, however, specific features that can be leveraged. Inspired by results that suggest that kinematic features alone are discriminant for specific actions, this work proposes a novel method which uses extreme acceleration patterns as the main feature. These extreme accelerations are efficiently estimated by applying the Radon transform to the power spectrum of consecutive frames. Experiments show that accuracy improvements of up to 12% are achieved with respect to state-of-the-art action recognition methods. Most importantly, the proposed method is at least 15 times faster.

Paper Citation

in Harvard Style

Deniz O., Serrano I., Bueno G. and Kim T. (2014). Fast Violence Detection in Video . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 478-485. DOI: 10.5220/0004695104780485

in Bibtex Style

@conference{visapp14,
author={Oscar Deniz and Ismael Serrano and Gloria Bueno and Tae-Kyun Kim},
title={Fast Violence Detection in Video},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={478-485},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004695104780485},
isbn={978-989-758-004-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Fast Violence Detection in Video
SN - 978-989-758-004-8
AU - Deniz O.
AU - Serrano I.
AU - Bueno G.
AU - Kim T.
PY - 2014
SP - 478
EP - 485
DO - 10.5220/0004695104780485