A Method Based on Dense Trajectory for Violent Video Classification
Nan Wang, Wei Song, Jianjun Hou, Jing Yu
Available Online December 2016.
- 10.2991/mcei-16.2016.163How to use a DOI?
- Gradient; Optical flow; Dense trajectory; Extreme learning machine; Bag of words
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.
- © 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/).
Cite this article
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 -