{"title":"A Novel Facial Appearance Descriptor Based on Local Binary Pattern","authors":"Shihu Zhu, Jufu Feng","doi":"10.1109/CCPR.2008.58","DOIUrl":null,"url":null,"abstract":"One of the key challenges for face recognition is finding efficient and discriminative facial appearance descriptors that are resistant to large variations in illumination, pose, face expression, ageing, face misalignment and other changes. In this paper, we propose a novel facial appearance descriptor based on local binary pattern (LBP), which presents several advantages. (1) It is more discriminative. (2) It is not sensitive to variations in illumination, pose, face expression, ageing and face misalignment. (3) It can be computed very efficiently and the feature sets are low-dimensional. Experiments on FERET database show that the proposed operator significantly outperforms other feature descriptors.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"239 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Chinese Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPR.2008.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
One of the key challenges for face recognition is finding efficient and discriminative facial appearance descriptors that are resistant to large variations in illumination, pose, face expression, ageing, face misalignment and other changes. In this paper, we propose a novel facial appearance descriptor based on local binary pattern (LBP), which presents several advantages. (1) It is more discriminative. (2) It is not sensitive to variations in illumination, pose, face expression, ageing and face misalignment. (3) It can be computed very efficiently and the feature sets are low-dimensional. Experiments on FERET database show that the proposed operator significantly outperforms other feature descriptors.