Christian A. Schneider, Natascha Esau, L. Kleinjohann, B. Kleinjohann
{"title":"Feature based Face Localization and Recognition on Mobile Devices","authors":"Christian A. Schneider, Natascha Esau, L. Kleinjohann, B. Kleinjohann","doi":"10.1109/ICARCV.2006.345308","DOIUrl":null,"url":null,"abstract":"Due to increasing miniaturization and decreasing prizes of cameras more and more mobile devices like PDAs or smartphones are equipped with a camera. Due to this fact, mobile face recognition will gain popularity in identifying persons e.g. in order to prevent unauthorized use or access to data and equipment. In this paper, the feature based face localization and recognition system FaceScry is presented. In spite of the limited resources available on mobile devices, FaceScry is able to localize an arbitrary number of faces with different sizes in images taken under varying illumination conditions in real-time. Also face recognition is size invariant due to the selected set of features, which mainly consists of angles and cross ratios. Since it stores reference face data for recognition as feature vectors and not as huge image data, FaceScry also allows for keeping a reasonable personal face data base for recognizing a set of persons on the smartphone","PeriodicalId":415827,"journal":{"name":"2006 9th International Conference on Control, Automation, Robotics and Vision","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 9th International Conference on Control, Automation, Robotics and Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2006.345308","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
Due to increasing miniaturization and decreasing prizes of cameras more and more mobile devices like PDAs or smartphones are equipped with a camera. Due to this fact, mobile face recognition will gain popularity in identifying persons e.g. in order to prevent unauthorized use or access to data and equipment. In this paper, the feature based face localization and recognition system FaceScry is presented. In spite of the limited resources available on mobile devices, FaceScry is able to localize an arbitrary number of faces with different sizes in images taken under varying illumination conditions in real-time. Also face recognition is size invariant due to the selected set of features, which mainly consists of angles and cross ratios. Since it stores reference face data for recognition as feature vectors and not as huge image data, FaceScry also allows for keeping a reasonable personal face data base for recognizing a set of persons on the smartphone