FACE VALIDATION WITH FACIAL MODEL USING GENETIC ALGORITHMS

摘要：

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.

关键词： Genetic algorithm Fitness Face detection Face validation

作者: CHENG-YUAN TANG YI-LEH WU HUI-WEN JENG WEN-CHAO CHEN

作者单位: Department of Information Management, Huafan University, Taipei, Taiwan Department of Computer Science and Information Engineering, National Taiwan University of Science an Electronics and Optoelectronics Research Laboratories, ITRI, Hsinchu, Taiwan

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1790-1795

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）