{"title":"基于l1的增广拉格朗日乘子法光度立体","authors":"Kyungdon Joo, Tae-Hyun Oh, In-So Kweon","doi":"10.1109/URAI.2013.6677405","DOIUrl":null,"url":null,"abstract":"Recently, the sparsity model has been applied to photometric stereo by modeling non-Lambertian artifacts as sparse components. As one of these efforts, we present l1-based photometric stereo for the non-Lambertian corruptions. A solution method was derived using the Augmented Lagrange Multiplier (ALM) method, which effectively solves the constrained problem by solving the sub-problems for surface normal and sparse corruptions iteratively. Experiments demonstrate the applicability of our method by comparing with the Least Square method and the l1 baseline method.","PeriodicalId":431699,"journal":{"name":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"L1-based photometric stereo via augmented lagrange multiplier method\",\"authors\":\"Kyungdon Joo, Tae-Hyun Oh, In-So Kweon\",\"doi\":\"10.1109/URAI.2013.6677405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, the sparsity model has been applied to photometric stereo by modeling non-Lambertian artifacts as sparse components. As one of these efforts, we present l1-based photometric stereo for the non-Lambertian corruptions. A solution method was derived using the Augmented Lagrange Multiplier (ALM) method, which effectively solves the constrained problem by solving the sub-problems for surface normal and sparse corruptions iteratively. Experiments demonstrate the applicability of our method by comparing with the Least Square method and the l1 baseline method.\",\"PeriodicalId\":431699,\"journal\":{\"name\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2013.6677405\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2013.6677405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
L1-based photometric stereo via augmented lagrange multiplier method
Recently, the sparsity model has been applied to photometric stereo by modeling non-Lambertian artifacts as sparse components. As one of these efforts, we present l1-based photometric stereo for the non-Lambertian corruptions. A solution method was derived using the Augmented Lagrange Multiplier (ALM) method, which effectively solves the constrained problem by solving the sub-problems for surface normal and sparse corruptions iteratively. Experiments demonstrate the applicability of our method by comparing with the Least Square method and the l1 baseline method.