NDLI: Towards facial feature extraction and verification for omni-face detection in video/images

Content Provider	IEEE Xplore Digital Library
Author	Xingquan Zhu Jianping Fan Elmagarmid, A.K.
Copyright Year	2002
Description	Author affiliation: Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA (Xingquan Zhu)
Abstract	Face detection is important in video/image content analysis and organization since the most important object in those media is often a human being. We propose a facial feature based omni-face detection algorithm. While utilizing the skin color model for face cue detection, a pairwise skin region refinement strategy is applied to eliminate the errors incurred by the skin model. Then, a region based adaptive threshold selection scheme is employed for facial feature segmentation. After the facial feature filtering, an orientation, pose and scale invariant face verification strategy is utilized to verify the detected face candidate regions. Experimental results demonstrate successful detection over a wide variety of facial variation in background, scale, view and orientation from different types of video collections.
Sponsorship	IEEE Signal Process. Soc
File Size	444693
File Format	PDF
ISBN	0780376226
ISSN	15224880
DOI	10.1109/ICIP.2002.1039900
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-09-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Facial features Face detection Skin Pixel Computer science Video sequences Lighting Object detection Humans Detection algorithms
Content Type	Text
Resource Type	Article

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