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Journal of Software:2013.24(11):2747-2757

基于局部区域稀疏编码的人脸检测
张抒,蔡勇,解梅
(电子科技大学 电子工程学院, 四川 成都 611731;电子科技大学 电子工程学院, 四川 成都 611731;空军工程大学 信息与导航学院, 陕西 西安 710071)
Face Detection Based on Local Region Sparse Coding
ZHANG Shu,CAI Yong,XIE Mei
(School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;School of Information and Navigation, Air Force Engineering University, Xi'an 710071, China)
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Received:May 28, 2013    Revised:July 17, 2013
> 中文摘要: 提出一种基于局部区域稀疏编码的人脸检测方法.首先提取人脸局部区域作为训练样本;然后学习得到一个具有较强判别性的字典,字典中的每个基与人脸各局部区域有明确的对应关系;接着,基于各检测窗口稀疏编码的响应判断人脸某一局部区域是否出现;最后,利用人脸局部区域的检测结果和位置约束进行投票,完成人脸定位.该方法的创新在于将稀疏编码和基于部件模型的思想相结合,实现人脸检测.在Caltech 和BioID 人脸数据库的实验结果表明:该方法适用于小样本问题,且在遮挡、复杂表情、人脸偏转等情况下具有较好的检测效果.
Abstract:In this paper, a face detection method based on local region sparse coding is proposed. First, every local face regions are extracted as training sample. Next, a discriminative dictionary whose atoms have explicit relations with local regions is learned. Then the appearance of a particular local region is determined based on the response of its sparse coding for each detection window. Finally, face location is obtained using position constraints and detection results of local regions. The innovation of the proposed method lies in combining sparse coding and part based model for face detection. Experimental results in Caltech and BioID database show that the proposed method is suitable for small sample size problem and has good detection results in case of occlusion, rotation, complex expressions.
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基金项目:国家自然科学基金(61271288);广东省自然科学基金(8152840301000009) 国家自然科学基金(61271288);广东省自然科学基金(8152840301000009)
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张抒,蔡勇,解梅.基于局部区域稀疏编码的人脸检测.软件学报,2013,24(11):2747-2757

ZHANG Shu,CAI Yong,XIE Mei.Face Detection Based on Local Region Sparse Coding.Journal of Software,2013,24(11):2747-2757