A robust face detection scheme for surveillance applications

Authors:
Sunghoon Kim;Hoon Lee;Soonyoung Park;Kyoungho Choi;JeongHyun Hwang
Affiliations:
Mokpo National Univ., Yongtonggu, Suwon, South Korea;Mokpo National Univ., Yongtonggu, Suwon, South Korea;Mokpo National Univ., Yongtonggu, Suwon, South Korea;Mokpo National Univ., Yongtonggu, Suwon, South Korea;Eyenix Co., Yongtonggu, Suwon, South Korea
Venue:
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
Year:
2008

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Abstract

In this paper, we present a framework to detect multiple faces with different sizes for surveillance applications, which is based on a fast moving object extraction approach followed by a skin color filtering and support vector machines. More specifically, moving objects are extracted first by using image difference between two consecutive frames and a simple object filling algorithm. Then, a skin color filtering combined with an eye detection algorithm is applied to locate possible face regions. Lastly, support vector machines are used to detect faces, which is applicable to detect faces with different sizes. Experimental results are provided to show that the proposed framework is applicable for surveillance applications.