Abstract
The localization of human faces in digital images is a fundamental step in the process of face recognition. This paper presents a shape comparison approach to achieve fast, accurate face detection that is robust to changes in illumination and background. The proposed method is edge-based and works on grayscale still images. The Hausdorff distance is used as a similarity measure between a general face model and possible instances of the object within the image. The paper describes an efficient implementation, making this approach suitable for real-time applications. A two-step process that allows both coarse detection and exact localization of faces is presented. Experiments were performed on a large test set base and rated with a new validation measurement.
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© 2001 Springer-Verlag Berlin Heidelberg
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Jesorsky, O., Kirchberg, K.J., Frischholz, R.W. (2001). Robust Face Detection Using the Hausdorff Distance. In: Bigun, J., Smeraldi, F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45344-X_14
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DOI: https://doi.org/10.1007/3-540-45344-X_14
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Online ISBN: 978-3-540-45344-4
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