{"title":"Deep feature-based face detection on mobile devices","authors":"Sayantan Sarkar, Vishal M. Patel, R. Chellappa","doi":"10.1109/ISBA.2016.7477230","DOIUrl":null,"url":null,"abstract":"We propose a deep feature-based face detector for mobile devices to detect user's face acquired by the front-facing camera. The proposed method is able to detect faces in images containing extreme pose and illumination variations as well as partial faces. The main challenge in developing deep feature-based algorithms for mobile devices is the constrained nature of the mobile platform and the non-availability of CUDA enabled GPUs on such devices. Our implementation takes into account the special nature of the images captured by the front-facing camera of mobile devices and exploits the GPUs present in mobile devices without CUDA-based frameworks, to meet these challenges.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBA.2016.7477230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
Abstract
We propose a deep feature-based face detector for mobile devices to detect user's face acquired by the front-facing camera. The proposed method is able to detect faces in images containing extreme pose and illumination variations as well as partial faces. The main challenge in developing deep feature-based algorithms for mobile devices is the constrained nature of the mobile platform and the non-availability of CUDA enabled GPUs on such devices. Our implementation takes into account the special nature of the images captured by the front-facing camera of mobile devices and exploits the GPUs present in mobile devices without CUDA-based frameworks, to meet these challenges.