Open Access

Face Detection Using a First-Order RCE Classifier

EURASIP Journal on Advances in Signal Processing20032003:297243

DOI: 10.1155/S1110865703304123

Received: 9 September 2002

Published: 18 August 2003


We present a new face detection algorithm based on a first-order reduced Coulomb energy (RCE) classifier. The algorithm locates frontal views of human faces at any degree of rotation and scale in complex scenes. The face candidates and their orientations are first determined by computing the Hausdorff distance between simple face abstraction models and binary test windows in an image pyramid. Then, after normalizing the energy, each face candidate is verified by two subsequent classifiers: a binary image classifier and the first-order RCE classifier. While the binary image classifier is employed as a preclassifier to discard nonfaces with minimum computational complexity, the first-order RCE classifier is used as the main face classifier for final verification. An optimal training method to construct the representative face model database is also presented. Experimental results show that the proposed algorithm yields a high detection ratio while yielding no false alarm.


face detection face model Hausdorff distance clustering algorithm RCE claassifier

Authors’ Affiliations

Signal Processing Laboratory, School of Electrical Engineering, Seoul National University
Institute of Intelligent Systems, Mechatronics Center, Samsung Electronics Co., Ltd.
Department of Electronics and Electrical Engineering, Hong-Ik University


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