• Title/Summary/Keyword: Facial Region Tracking

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Adaptive Skin Color Segmentation in a Single Image using Image Feedback (영상 피드백을 이용한 단일 영상에서의 적응적 피부색 검출)

  • Do, Jun-Hyeong;Kim, Keun-Ho;Kim, Jong-Yeol
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.3
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    • pp.112-118
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    • 2009
  • Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.

Wavelet Transform-based Face Detection for Real-time Applications (실시간 응용을 위한 웨이블릿 변환 기반의 얼굴 검출)

  • 송해진;고병철;변혜란
    • Journal of KIISE:Software and Applications
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    • v.30 no.9
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    • pp.829-842
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    • 2003
  • In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.