NDLI: Integrated Detect-Track Framework for Multi-view Face Detection in Video

Content Provider	IEEE Xplore Digital Library
Author	Anoop, K.R. Anandathirtha, P. Ramakrishnan, K.R. Kankanhalli, M.S.
Copyright Year	2008
Description	Author affiliation: Dept of Electr. Eng., Indian Inst. of Sci., Bangalore (Anoop, K.R.; Anandathirtha, P.; Ramakrishnan, K.R.) \|\| Sch. of Comput., Nat. Univ. of Singapore, Singapore (Kankanhalli, M.S.)
Abstract	An Experiential sampling and Meanshift tracker based Multi-view face detection in video is proposed in this paper. In this framework, instead of performing face detection at every position in a frame, we determine certain key positions to run the multi-view face detectors. These key positions are statistical samples drawn from a density function that is estimated based on color cues, past detection results, Meanshift tracker results and a temporal continuity model. These samples are then propogated using a Particle filter framework. We use a Meanshift tracker to track faces that are missed by the multiview face detectors. Our framework results in a significant reduction in computation time and accounts for the detection of complete 180 degree pose of the face. We also come up with a novel likelihood measure for track termination, which becomes important when used for detection purposes.
Starting Page	336
Ending Page	343
File Size	1266672
Page Count	8
File Format	PDF
ISBN	9780769534763
DOI	10.1109/ICVGIP.2008.91
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Experiential Computer vision Tracking Image processing Image sampling Face detection Videoconference Multiview Particle Detectors Computer graphics TBD Density functional theory Robustness Particle filters Detect-track Face Detection Meanshift
Content Type	Text
Resource Type	Article

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