计算机科学 ›› 2017, Vol. 44 ›› Issue (3): 296-299.doi: 10.11896/j.issn.1002-137X.2017.03.060
首照宇,杨晓帆
SHOU Zhao-yu and YANG Xiao-fan
摘要： 针对人脸图片的遮挡、伪装、光照及表情变化等问题,根据Gabor特征对遮挡、伪装、光照及表情变化有着更强的鲁棒性的特点,提出了联合Gabor误差字典和低秩表示的人脸识别算法(GDLRR)。首先对训练样本和测试样本分别进行Gabor特征提取,并将这些特征组成待测试的特征字典；然后将一个单位阵进行Gabor特征提取并训练成一个更紧凑的Gabor误差字典；最后联合Gabor误差字典和训练特征字典对测试特征字典进行低秩表示后进行分类识别。各类实验表明,提出的改进算法对人脸识别的各类问题都有着更强的鲁棒性和更高的识别准确率。
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