A Method Based on Dense Trajectory for Violent Video Classification

DOI

10.2991/mcei-16.2016.163How to use a DOI?

Keywords

Gradient; Optical flow; Dense trajectory; Extreme learning machine; Bag of words

Abstract

At present, the internet technology develops so rapidly and the video becomes the major component of the internet traffic. The content security of massive public videos is an important factor to the social stability. Among them, violent video is an important class of unsafe videos. We proposed a novel method based on dense trajectory and extreme learning machine to recognize them. The spatial-temporal characteristics were well expressed by the use of optical flow and gradient. The experiment on the benchmark dataset named Movies indicated our proposed method had a better accuracy than the state-of-the-art methods. Our proposed method is an efficient method for violent video classification.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nan Wang
AU  - Wei Song
AU  - Jianjun Hou
AU  - Jing Yu
PY  - 2016/12
DA  - 2016/12
TI  - A Method Based on Dense Trajectory for Violent Video Classification
BT  - Proceedings of the 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
PB  - Atlantis Press
SP  - 781
EP  - 786
SN  - 1951-6851
UR  - https://doi.org/10.2991/mcei-16.2016.163
DO  - 10.2991/mcei-16.2016.163
ID  - Wang2016/12
ER  -