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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 Hausdor# 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... (Update)
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BibTeX entry: (Update)
O. Jesorsky, K. Kirchberg, and R. Frischholz, `Robust face detection using the Hausdorff distance', in Proc. of the 3rd International Conference on Audio and Video based Person Authentication, pp. 90--95. Springer, LNCS-2091. http://citeseer.ist.psu.edu/jesorsky01robust.html More
@inproceedings{ jesorsky01robust,
author = "Oliver Jesorsky and Klaus J. Kirchberg and Robert W. Frischholz",
title = "{R}obust {F}ace {D}etection {U}sing the {H}ausdorff {D}istance",
booktitle = "Audio- and Video-Based Person Authentication - {AVBPA} 2001",
volume = "2091",
publisher = "Springer",
address = "Halmstad, Sweden",
editor = "Josef Bigun and Fabrizio Smeraldi",
pages = "90--95",
year = "2001",
url = "citeseer.ist.psu.edu/jesorsky01robust.html" }
Citations (may not include all citations):335 Neural network-based face detection - Rowley, Baluja et al. - 1996
50 XMVTSDB extended MVT database - Kittler, Maitre et al. - 1999
15 Automatic detection of human faces in natural scene images b.. - Terrillon, David et al. - 1998
9 distance for object matching (context) - Dubuisson, Jain et al. - 1994
7 cient Visual Recognition Using the Hausdor# Distance (context) - Rucklidge - 1996
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