DocumentCode :
467797
Title :
Face Validation with Facial Model using Genetic Algorithms
Author :
Cheng-Yuan Tang ; Yi-Leh Wu ; Hui-Wen Jeng ; Wen-Chao Chen
Author_Institution :
Huafan Univ., Taipei
Volume :
3
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
1790
Lastpage :
1795
Abstract :
In this paper, the Genetic Algorithms (GA) is used to learn the facial model consisting of eyes, nose and mouth for face validation. This facial model improves the detection rate for the Maximum-Likelihood (ML) head detector [9], which produces ellipse-like objects as face candidates, by applying a second validation stage to verify these candidates. In formulating the genetic algorithm, a two-dimensional binary genome mapped from the facial images is used to encode the chromosomes. We also propose to employ properties, such as the eye position and the eye-point preservation, to evaluate the fitness in the genetic algorithm. We demonstrate the experimental results of using two initialization models, namely the blank model and the average edge model, to learn the facial model for face validation.
Keywords :
face recognition; genetic algorithms; image coding; maximum likelihood detection; average edge model; blank model; chromosome encoding; ellipse-like object; eye position; eye-point preservation; face validation; facial image model; genetic algorithm; maximum-likelihood head detection; Detectors; Eyes; Face detection; Genetic algorithms; Genomics; Head; Maximum likelihood detection; Mouth; Nose; Object detection; Face detection; Face validation; Fitness; Genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0972-3
Type :
conf
DOI :
10.1109/ICMLC.2007.4370438
Filename :
4370438
Link To Document :
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