Title :
Face recognition by fiducial point analysis
Author :
Ersi, Ehsan Fazl ; Hajebi, Kiana
Author_Institution :
Dept. of Comput. Eng., Azad Univ. of Mashad, Iran
Abstract :
In this paper we present a hybrid method for face recognition task, which covers both the important information in the high order relationships among the image pixels and low dimensional representation of the image. This system is feature based, and analyzes local facial features, which are located by a meta-version of the sparsification algorithm in the context of LFA (local feature analysis) technique. The LFA sparsification strategy reduces the dimensionality of the representation by choosing a subset of output points that are as decorrelated as possible. Since choosing different set of points for each image, will make a problem in recognition, we determined a single set of points for all images which called fiducial points, and propose a method based on genetic algorithm to find them in any face image. After extracting fiducial points, we describe each of them with a set of Gabor coefficients to make a unique ID for each new face.
Keywords :
face recognition; feature extraction; genetic algorithms; image representation; principal component analysis; Gabor coefficient; LFA technique; ORL face bank; face recognition; feature extraction; fiducial point analysis; genetic algorithm; image representation; jet; local feature analysis; principal component analysis; sparsification algorithm; Algorithm design and analysis; Face recognition; Facial features; Feature extraction; Genetic algorithms; Image analysis; Image recognition; Pattern analysis; Pixel; Principal component analysis;
Conference_Titel :
Electrical and Computer Engineering, 2003. IEEE CCECE 2003. Canadian Conference on
Print_ISBN :
0-7803-7781-8
DOI :
10.1109/CCECE.2003.1226110