The back of the mirror is mainly decorated with dragon patterns,in which the head of the dragon is perking up.and the body of the dragon stretches freely.This is the largest ancient copper mirror ever seen.The bronze ...The back of the mirror is mainly decorated with dragon patterns,in which the head of the dragon is perking up.and the body of the dragon stretches freely.This is the largest ancient copper mirror ever seen.The bronze mirror is used to reflect the human image.SO the surface must be bright and fiat.For sucha casting with a large flat surface,it is extremely difficult to control the mirror surface without warpingdeformation.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The back of the mirror is mainly decorated with dragon patterns,in which the head of the dragon is perking up.and the body of the dragon stretches freely.This is the largest ancient copper mirror ever seen.The bronze mirror is used to reflect the human image.SO the surface must be bright and fiat.For sucha casting with a large flat surface,it is extremely difficult to control the mirror surface without warpingdeformation.
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.
基金The Program for the New Century Excellent Talents in University,Ministry of Education of China(No.NCET-10-0075)the National Natural Science Foundation of China(No.50805123
