{"title":"拟合三维密集面部模型到二维图像:无地标方法","authors":"Yuhang Wu, Xiang Xu, S. Shah, I. Kakadiaris","doi":"10.1109/BTAS.2015.7358799","DOIUrl":null,"url":null,"abstract":"Head pose estimation helps to align a 3D face model to a 2D image, which is critical to research requiring dense 2D-to-2D or 3D-to-2D correspondence. Traditional pose estimation relies strongly on the accuracy of landmarks, so it is sensitive to missing or incorrect landmarks. In this paper, we propose a landmark-free approach to estimate the pose projection matrix. The method can be used to estimate this matrix in unconstrained scenarios and we demonstrate its effectiveness through multiple head pose estimation experiments.","PeriodicalId":404972,"journal":{"name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","volume":"30 14","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Towards fitting a 3D dense facial model to a 2D image: A landmark-free approach\",\"authors\":\"Yuhang Wu, Xiang Xu, S. Shah, I. Kakadiaris\",\"doi\":\"10.1109/BTAS.2015.7358799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Head pose estimation helps to align a 3D face model to a 2D image, which is critical to research requiring dense 2D-to-2D or 3D-to-2D correspondence. Traditional pose estimation relies strongly on the accuracy of landmarks, so it is sensitive to missing or incorrect landmarks. In this paper, we propose a landmark-free approach to estimate the pose projection matrix. The method can be used to estimate this matrix in unconstrained scenarios and we demonstrate its effectiveness through multiple head pose estimation experiments.\",\"PeriodicalId\":404972,\"journal\":{\"name\":\"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)\",\"volume\":\"30 14\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BTAS.2015.7358799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BTAS.2015.7358799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards fitting a 3D dense facial model to a 2D image: A landmark-free approach
Head pose estimation helps to align a 3D face model to a 2D image, which is critical to research requiring dense 2D-to-2D or 3D-to-2D correspondence. Traditional pose estimation relies strongly on the accuracy of landmarks, so it is sensitive to missing or incorrect landmarks. In this paper, we propose a landmark-free approach to estimate the pose projection matrix. The method can be used to estimate this matrix in unconstrained scenarios and we demonstrate its effectiveness through multiple head pose estimation experiments.