Abstract
Computer-based face perception is becoming increasingly important for many applications like biometric face recognition, video coding or multi-model human-machine interaction. Fast and robust detection and segmentation of a face in an unconstrained visual scene is a basic requirement for all kinds of face perception. This paper deals with the integration of three simple visual cues for the task of face detection in grey level images. It is achieved by a combination of edge orientation matching, hough transform and an appearance based detection method. The proposed system is computationally efficient and has proved to be robust under a wide range of acquisition conditions like varying lighting, pixel noise and other image distortions. The detection capabilities of the presented algorithm are evaluated on a large database of 13122 images including the frontal-face set of the m2vts database. We achieve a detection rate of over 91% on this database while having only few false detects at the same time.
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Fröba, B., Zink, W. (2001). On the Combination of Different Template Matching Strategies for Fast Face Detection. In: Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2001. Lecture Notes in Computer Science, vol 2096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48219-9_42
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DOI: https://doi.org/10.1007/3-540-48219-9_42
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