{"title":"从单个侧面图像中恢复正面姿态图像","authors":"Jianbo Ma, N. Ahuja, C. Neti, A. Senior","doi":"10.1109/ICIP.2000.899288","DOIUrl":null,"url":null,"abstract":"In appearance based face recognition, lip reading, etc., eigen face and eigen lip are used for recognition. The pose changes of the human head in a video sequence often cause errors in the eigen space comparison stage, because the frontal-pose assumption has been violated. We propose a new method to compensate the pose changes by exploiting the general symmetry of human face. From the imaging geometry we show that a frontal pose can be recovered from only one profile view. The resulting pose compensation method has the following advantages: (1) it only requires one profile image; (2) it does not need any 3D model; (3) it does not need accurate feature detection. Experimental results in the context of lip images are given to show the effectiveness of our method.","PeriodicalId":193198,"journal":{"name":"Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Recovering frontal-pose image from a single profile image\",\"authors\":\"Jianbo Ma, N. Ahuja, C. Neti, A. Senior\",\"doi\":\"10.1109/ICIP.2000.899288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In appearance based face recognition, lip reading, etc., eigen face and eigen lip are used for recognition. The pose changes of the human head in a video sequence often cause errors in the eigen space comparison stage, because the frontal-pose assumption has been violated. We propose a new method to compensate the pose changes by exploiting the general symmetry of human face. From the imaging geometry we show that a frontal pose can be recovered from only one profile view. The resulting pose compensation method has the following advantages: (1) it only requires one profile image; (2) it does not need any 3D model; (3) it does not need accurate feature detection. Experimental results in the context of lip images are given to show the effectiveness of our method.\",\"PeriodicalId\":193198,\"journal\":{\"name\":\"Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2000.899288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2000.899288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recovering frontal-pose image from a single profile image
In appearance based face recognition, lip reading, etc., eigen face and eigen lip are used for recognition. The pose changes of the human head in a video sequence often cause errors in the eigen space comparison stage, because the frontal-pose assumption has been violated. We propose a new method to compensate the pose changes by exploiting the general symmetry of human face. From the imaging geometry we show that a frontal pose can be recovered from only one profile view. The resulting pose compensation method has the following advantages: (1) it only requires one profile image; (2) it does not need any 3D model; (3) it does not need accurate feature detection. Experimental results in the context of lip images are given to show the effectiveness of our method.