2 research outputs found
vireoJD-MM at Activity Detection in Extended Videos
This notebook paper presents an overview and comparative analysis of our
system designed for activity detection in extended videos (ActEV-PC) in
ActivityNet Challenge 2019. Specifically, we exploit person/vehicle detections
in spatial level and action localization in temporal level for action detection
in surveillance videos. The mechanism of different tubelet generation and model
decomposition methods are studied as well. The detection results are finally
predicted by late fusing the results from each component
TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval
The TREC Video Retrieval Evaluation (TRECVID) 2019 was a TREC-style video
analysis and retrieval evaluation, the goal of which remains to promote
progress in research and development of content-based exploitation and
retrieval of information from digital video via open, metrics-based evaluation.
Over the last nineteen years this effort has yielded a better understanding of
how systems can effectively accomplish such processing and how one can reliably
benchmark their performance. TRECVID has been funded by NIST (National
Institute of Standards and Technology) and other US government agencies. In
addition, many organizations and individuals worldwide contribute significant
time and effort. TRECVID 2019 represented a continuation of four tasks from
TRECVID 2018. In total, 27 teams from various research organizations worldwide
completed one or more of the following four tasks: 1. Ad-hoc Video Search (AVS)
2. Instance Search (INS) 3. Activities in Extended Video (ActEV) 4. Video to
Text Description (VTT) This paper is an introduction to the evaluation
framework, tasks, data, and measures used in the workshop.Comment: TRECVID Workshop overview paper. 39 page