MMVG-INF-Etrol@ TRECVID 2019: Activities in Extended Video

Xiaojun Chang, Wenhe Liu, Po-Yao Huang, Changlin Li, Fengda Zhu, Mingfei Han, Mingjie Li, Mengyuan Ma, Siyi Hu, Guoliang Kang, Junwei Liang, Liangke Gui, Lijun Yu, Yijun Qian, Jing Wen, Alexander G. Hauptmann

Published in TRECVID, 2019

NIST

We propose a video analysis system detecting activities in surveillance scenarios which wins Trecvid Activities in Extended Video (ActEV1) challenge 2019. For detecting and localizing surveillance events in videos, Argus employs a spatial- temporal activity proposal generation module facilitating object detection and tracking, followed by a sequential classification module to spatially and temporally localize persons and objects involved in the activity. We detail the design challenges and provide our insights and solutions in developing the state-of-the-art surveillance video analysis system.

@inproceedings{changmmvg2019,
  title={ {MMVG-INF-Etrol}@ {TRECVID} 2019: Activities in Extended Video},
  author={Chang, Xiaojun and Liu, Wenhe and Huang, Po-Yao and Li, Changlin and Zhu, Fengda and Han, Mingfei and Li, Mingjie and Ma, Mengyuan and Hu, Siyi and Kang, Guoliang and others},
  booktitle={TRECVID},
  year={2019}
}