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 Hauptmann

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

3 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationTREDVID 2019
EditorsGeorge Awad
Place of PublicationSaarbrücken/Wadern Germany
PublisherSchloss Dagstuhl
Number of pages8
Publication statusPublished - 2019
EventTREC Video Retrieval Evaluation 2019 - Gaithersburg, United States of America
Duration: 12 Nov 201913 Nov 2019 (Proceedings) (Website)


ConferenceTREC Video Retrieval Evaluation 2019
Abbreviated titleTRECVID 2019
Country/TerritoryUnited States of America
Internet address

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