基于POEM_SLPP的人脸识别算法
发布时间：2018-10-08 15:35
【摘要】：针对方向边缘幅值模式(patterns of oriented edge magnitudes,POEM)提取的人脸特征维数过高和计算复杂度较大的问题,提出了结合方向边缘幅值模式和有监督的局部保持投影(patterns of oriented edge magnitudes_supervised locality preserving projections,POEM_SLPP)的人脸识别算法。首先,采用POEM算子进行特征提取;其次,将高维特征数据投影到SLPP算法求出的低维样本空间进行降维;最后,采用最近邻法对测试样本进行分类。在CAS-PEAL-R1人脸库上的实验结果表明,在表情、背景、饰物、时间、距离测试集上,该算法的平均识别率较POEM+LPP算法提高了22%,较POEM+PCA提高了2%。
[Abstract]:The dimension of face feature extracted by directional edge amplitude mode (patterns of oriented edge magnitudes,POEM) is too high and the computational complexity is large. A face recognition algorithm based on directional edge amplitude pattern and supervised local preserving projection (patterns of oriented edge magnitudes_supervised locality preserving projections,POEM_SLPP) is proposed. Firstly, POEM operator is used for feature extraction; secondly, the high-dimensional feature data is projected into the low-dimensional sample space of SLPP algorithm for dimensionality reduction; finally, the nearest neighbor method is used to classify the test samples. The experimental results on CAS-PEAL-R1 face database show that the average recognition rate of the algorithm is 22% higher than that of POEM LPP algorithm and 2% higher than that of POEM PCA in expression, background, ornaments, time and distance test sets.
【作者单位】： 上海电力学院自动化工程学院;
【基金】：上海市电站自动化技术重点实验室资助项目(13DZ2273800)
【分类号】：TP391.41
[Abstract]:The dimension of face feature extracted by directional edge amplitude mode (patterns of oriented edge magnitudes,POEM) is too high and the computational complexity is large. A face recognition algorithm based on directional edge amplitude pattern and supervised local preserving projection (patterns of oriented edge magnitudes_supervised locality preserving projections,POEM_SLPP) is proposed. Firstly, POEM operator is used for feature extraction; secondly, the high-dimensional feature data is projected into the low-dimensional sample space of SLPP algorithm for dimensionality reduction; finally, the nearest neighbor method is used to classify the test samples. The experimental results on CAS-PEAL-R1 face database show that the average recognition rate of the algorithm is 22% higher than that of POEM LPP algorithm and 2% higher than that of POEM PCA in expression, background, ornaments, time and distance test sets.
【作者单位】： 上海电力学院自动化工程学院;
【基金】：上海市电站自动化技术重点实验室资助项目(13DZ2273800)
【分类号】：TP391.41
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