Title: An automated feature-localisation algorithm for a feature-specific modular approach for face recognition
Authors: Praveen Sankaran, Rajkiran Gottumukkal, Vijayan K. Asari
Addresses: Department of ECE, Old Dominion University, 200, Kaufman Hall, Norfolk, VA 23529, USA. ' Department of ECE, Old Dominion University, 200, Kaufman Hall, Norfolk, VA 23529, USA. ' Department of ECE, Old Dominion University, 231, Kaufman Hall, Norfolk, VA 23529, USA
Abstract: Novel techniques for accurate location of the eyes and nose of a person in a complex-lighting environment are presented in this paper. An adaptive progressive thresholding technique is applied to spot the darkest regions representing the eyes in a face. The nose region is located by performing cumulative histogram-based thresholding of the gradient image formed below the eye region. A feature-specific modular Principal Component Analysis (PCA) approach on face images is performed with the identified features for face recognition. Principal components are extracted from non-overlapping modules of the image and are concatenated to make a single signature vector to represent the face in a particular viewing angle. Additional principal components are extracted from the key facial features and are added as an extension to the signature vector. The feature-specific modular PCA approach is capable of recognising faces in varying illumination conditions and facial expressions, as the modular components represent the local information of the facial regions.
Keywords: feature localisation; modular face recognition; Face Recognition Grand Challenge; FRGC; eyes location; nose location; complex lighting; principal component analysis; PCA; facial expressions.
International Journal of Intelligent Systems Technologies and Applications, 2007 Vol.2 No.4, pp.329 - 344
Published online: 12 Jun 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article