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http://dx.doi.org/10.5302/J.ICROS.2005.11.1.050

Face and Facial Feature Detection under Pose Variation of User Face for Human-Robot Interaction  

Park Sung-Kee (한국과학기술연구원 지능로봇연구센터)
Park Mignon (연세대학교 전기전자공학과)
Lee Taigun (연세대학교 전기전자공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.11, no.1, 2005 , pp. 50-57 More about this Journal
Abstract
We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.
Keywords
face and facial features detection; pose variation; edge-like blob map; directional template; eye pairs;
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