{"title":"An automatic facial feature point localization method","authors":"Qinyan Zhang, Xiaoping Li","doi":"10.1109/CCIS.2011.6045119","DOIUrl":null,"url":null,"abstract":"This paper proposes an automatic facial feature point localization method that based on calculating the similarity. In a complicated illumination condition, beard interference and small angle facial tilt, this system which mentioned in this paper is still robust. It is not necessary to train the sample set which localize the facial feature points manually. The experimental results demonstrate that this system have a good performance and high accuracy.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIS.2011.6045119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes an automatic facial feature point localization method that based on calculating the similarity. In a complicated illumination condition, beard interference and small angle facial tilt, this system which mentioned in this paper is still robust. It is not necessary to train the sample set which localize the facial feature points manually. The experimental results demonstrate that this system have a good performance and high accuracy.
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