三维人脸数据的获取会受到成本以及可访问性的影响。通过对深度相机(如Xtion pro live)获取人脸数据过程的研究可知,它能够很容易获得彩色和深度结合(RGB-D)图。针对RGB-D图,使用局部和整体混合识别,利用局部二值的平均信息熵模式(LBEP)...三维人脸数据的获取会受到成本以及可访问性的影响。通过对深度相机(如Xtion pro live)获取人脸数据过程的研究可知,它能够很容易获得彩色和深度结合(RGB-D)图。针对RGB-D图,使用局部和整体混合识别,利用局部二值的平均信息熵模式(LBEP),快速提取RGB-D图的直方图信息和特征向量,根据不同区域在表情不同情况下的变化程度,对不同区域的识别效果赋予不同的权值,进行加权运算。实验结果表明,相比现有的二维和三维人脸识别算法,改进的LBEP算法识别率有明显的提升。展开更多
针对跨年龄人脸验证任务中面部纹理、形状特征变化的问题,提出一种基于双编码平均局部二值模式(dual-coded average local binary pattern,DCALBP)与深度学习算法相结合的多任务人脸验证算法。首先,使用多任务卷积神经网络(multi-task c...针对跨年龄人脸验证任务中面部纹理、形状特征变化的问题,提出一种基于双编码平均局部二值模式(dual-coded average local binary pattern,DCALBP)与深度学习算法相结合的多任务人脸验证算法。首先,使用多任务卷积神经网络(multi-task convolutional neural network,MTCNN)对人脸检测图片进行预处理,引入双编码平均局部二值模式(DCALBP)和梯度直方图算法(histogram of oriented gradient,HOG)提取人脸的局部纹理特征和形状特征,运用典型相关性分析(canonical correlation analysis,CCA)算法将两种特征融合,得到人脸年龄特征。然后,孪生网络(siamese network)提取人脸面部特征,并将纹理形状特征从中分离,抑制年龄因素对人脸验证的影响,从而得到具有年龄不变性的人脸特征。最后进行人脸特征匹配,实现跨年龄人脸验证。通过在数据集FG-NET、MORPH Album2以及经过处理的综合数据集上进行实验,准确率分别为89.73%、98.32%和98.27%,充分验证了该方法的有效性。展开更多
This paper presents a new feature descriptor, namely local extreme complete trio pattern (LECTP) for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible direc...This paper presents a new feature descriptor, namely local extreme complete trio pattern (LECTP) for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible directions using trio values. The LECTP integrates the local extreme sign trio patterns (LESTP) with magnitude local operator (MLOP) for image retrieval. The performance of the LECTP is tested by conducting three experiments on Corel-5 000, Corel-10 000 and MIT-VisTex color databases, respectively. The results after investigation show a significant improvement in terms of average retrieval precision (ARP) and average retrieval rate (ARR) as compared to the other state-of-the art techniques in content based image retrieval (CBIR).展开更多
Face recognition(FR) is a practical application of pattern recognition(PR) and remains a compelling topic in the study of computer vision. However, in real-world FR systems, interferences in images, including illumina...Face recognition(FR) is a practical application of pattern recognition(PR) and remains a compelling topic in the study of computer vision. However, in real-world FR systems, interferences in images, including illumination condition, occlusion, facial expression and pose variation, make the recognition task challenging. This study explored the impact of those interferences on FR performance and attempted to alleviate it by taking face symmetry into account. A novel and robust FR method was proposed by combining multi-mirror symmetry with local binary pattern(LBP), namely multi-mirror local binary pattern(MMLBP). To enhance FR performance with various interferences, the MMLBP can 1) adaptively compensate lighting under heterogeneous lighting conditions, and 2) generate extracted image features that are much closer to those under well-controlled conditions(i.e., frontal facial images without expression). Therefore, in contrast with the later variations of LBP, the symmetrical singular value decomposition representation(SSVDR) algorithm utilizing the facial symmetry and a state-of-art non-LBP method, the MMLBP method is shown to successfully handle various image interferences that are common in FR applications without preprocessing operation and a large number of training images. The proposed method was validated with four public data sets. According to our analysis, the MMLBP method was demonstrated to achieve robust performance regardless of image interferences.展开更多
文摘三维人脸数据的获取会受到成本以及可访问性的影响。通过对深度相机(如Xtion pro live)获取人脸数据过程的研究可知,它能够很容易获得彩色和深度结合(RGB-D)图。针对RGB-D图,使用局部和整体混合识别,利用局部二值的平均信息熵模式(LBEP),快速提取RGB-D图的直方图信息和特征向量,根据不同区域在表情不同情况下的变化程度,对不同区域的识别效果赋予不同的权值,进行加权运算。实验结果表明,相比现有的二维和三维人脸识别算法,改进的LBEP算法识别率有明显的提升。
文摘针对跨年龄人脸验证任务中面部纹理、形状特征变化的问题,提出一种基于双编码平均局部二值模式(dual-coded average local binary pattern,DCALBP)与深度学习算法相结合的多任务人脸验证算法。首先,使用多任务卷积神经网络(multi-task convolutional neural network,MTCNN)对人脸检测图片进行预处理,引入双编码平均局部二值模式(DCALBP)和梯度直方图算法(histogram of oriented gradient,HOG)提取人脸的局部纹理特征和形状特征,运用典型相关性分析(canonical correlation analysis,CCA)算法将两种特征融合,得到人脸年龄特征。然后,孪生网络(siamese network)提取人脸面部特征,并将纹理形状特征从中分离,抑制年龄因素对人脸验证的影响,从而得到具有年龄不变性的人脸特征。最后进行人脸特征匹配,实现跨年龄人脸验证。通过在数据集FG-NET、MORPH Album2以及经过处理的综合数据集上进行实验,准确率分别为89.73%、98.32%和98.27%,充分验证了该方法的有效性。
文摘This paper presents a new feature descriptor, namely local extreme complete trio pattern (LECTP) for image retrieval application. The LECTP extracts complete extreme to minimal edge information in all possible directions using trio values. The LECTP integrates the local extreme sign trio patterns (LESTP) with magnitude local operator (MLOP) for image retrieval. The performance of the LECTP is tested by conducting three experiments on Corel-5 000, Corel-10 000 and MIT-VisTex color databases, respectively. The results after investigation show a significant improvement in terms of average retrieval precision (ARP) and average retrieval rate (ARR) as compared to the other state-of-the art techniques in content based image retrieval (CBIR).
基金supported by National Natural Science Foundation of China (No. 51305392)Youth Funds of the State Key Laboratory of Fluid Power Transmission and Control (No. SKLoFP_QN_1501)+1 种基金Zhejiang Provincial Natural Science Foundation of China (Nos. LY17E050009 and LZ15E050001)the Fundamental Rsesearch Funds for the Central Universities (No. 2018QNA4008)
文摘Face recognition(FR) is a practical application of pattern recognition(PR) and remains a compelling topic in the study of computer vision. However, in real-world FR systems, interferences in images, including illumination condition, occlusion, facial expression and pose variation, make the recognition task challenging. This study explored the impact of those interferences on FR performance and attempted to alleviate it by taking face symmetry into account. A novel and robust FR method was proposed by combining multi-mirror symmetry with local binary pattern(LBP), namely multi-mirror local binary pattern(MMLBP). To enhance FR performance with various interferences, the MMLBP can 1) adaptively compensate lighting under heterogeneous lighting conditions, and 2) generate extracted image features that are much closer to those under well-controlled conditions(i.e., frontal facial images without expression). Therefore, in contrast with the later variations of LBP, the symmetrical singular value decomposition representation(SSVDR) algorithm utilizing the facial symmetry and a state-of-art non-LBP method, the MMLBP method is shown to successfully handle various image interferences that are common in FR applications without preprocessing operation and a large number of training images. The proposed method was validated with four public data sets. According to our analysis, the MMLBP method was demonstrated to achieve robust performance regardless of image interferences.