M. Zobel, A. Gebhard, D. Paulus, Joachim Denzler, H. Niemann
{"title":"Robust facial feature localization by coupled features","authors":"M. Zobel, A. Gebhard, D. Paulus, Joachim Denzler, H. Niemann","doi":"10.1109/AFGR.2000.840604","DOIUrl":null,"url":null,"abstract":"We consider the problem of robust localization of faces and some of their facial features. The task arises, e.g., in the medical field of visual analysis of facial paresis. We detect faces and facial features by means of appropriate DCT coefficients that we obtain by neatly using the coding capabilities of a JPEG hardware compressor. Beside an anthropometric localization approach we focus on how spatial coupling of the facial features can be used to improve robustness of the localization. Because the presented approach is embedded in a completely probabilistic framework, it is not restricted to facial features, it can be generalized to multipart objects of any kind. Therefore the notion of a \"coupled structure\" is introduced. Finally, the approach is applied to the problem of localizing facial features in DCT-coded images and results from our experiments are shown.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"120 1-3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AFGR.2000.840604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
We consider the problem of robust localization of faces and some of their facial features. The task arises, e.g., in the medical field of visual analysis of facial paresis. We detect faces and facial features by means of appropriate DCT coefficients that we obtain by neatly using the coding capabilities of a JPEG hardware compressor. Beside an anthropometric localization approach we focus on how spatial coupling of the facial features can be used to improve robustness of the localization. Because the presented approach is embedded in a completely probabilistic framework, it is not restricted to facial features, it can be generalized to multipart objects of any kind. Therefore the notion of a "coupled structure" is introduced. Finally, the approach is applied to the problem of localizing facial features in DCT-coded images and results from our experiments are shown.