{"title":"基于头部姿态估计的无标记AR系统鲁棒实时人脸跟踪","authors":"Márcio C. F. Macedo, A. Apolinario, A. Souza","doi":"10.1109/SVR.2013.12","DOIUrl":null,"url":null,"abstract":"In this paper we present an extension to the Kinect- Fusion algorithm that allows a robust real-time face tracking. This is achieved altering the original algorithm such that when the tracking algorithm fails, it uses a head pose estimation to give an initial guess to the Iterative Closest Point (ICP) algorithm. We show that this approach can handle more face pose changes and variations than the original KinectFusion's tracking.","PeriodicalId":189272,"journal":{"name":"2013 XV Symposium on Virtual and Augmented Reality","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"A Robust Real-Time Face Tracking Using Head Pose Estimation for a Markerless AR System\",\"authors\":\"Márcio C. F. Macedo, A. Apolinario, A. Souza\",\"doi\":\"10.1109/SVR.2013.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present an extension to the Kinect- Fusion algorithm that allows a robust real-time face tracking. This is achieved altering the original algorithm such that when the tracking algorithm fails, it uses a head pose estimation to give an initial guess to the Iterative Closest Point (ICP) algorithm. We show that this approach can handle more face pose changes and variations than the original KinectFusion's tracking.\",\"PeriodicalId\":189272,\"journal\":{\"name\":\"2013 XV Symposium on Virtual and Augmented Reality\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 XV Symposium on Virtual and Augmented Reality\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SVR.2013.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 XV Symposium on Virtual and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SVR.2013.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Robust Real-Time Face Tracking Using Head Pose Estimation for a Markerless AR System
In this paper we present an extension to the Kinect- Fusion algorithm that allows a robust real-time face tracking. This is achieved altering the original algorithm such that when the tracking algorithm fails, it uses a head pose estimation to give an initial guess to the Iterative Closest Point (ICP) algorithm. We show that this approach can handle more face pose changes and variations than the original KinectFusion's tracking.
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