{"title":"基于随机数据融合的摄像机姿态跟踪框架","authors":"Armaghan Moemeni, E. Tatham","doi":"10.1109/ICEGIC.2010.5716876","DOIUrl":null,"url":null,"abstract":"A novel camera pose tracking system using a stochastic inertial-visual sensor fusion has been proposed. A method based on the Particle Filtering concept has been adapted for inertial and vision data fusion, which benefits from the agility of inertial-based tracking and robustness of vision-based camera tracking.","PeriodicalId":229345,"journal":{"name":"2010 2nd International IEEE Consumer Electronics Society's Games Innovations Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A framework for camera pose tracking using stochastic data fusion\",\"authors\":\"Armaghan Moemeni, E. Tatham\",\"doi\":\"10.1109/ICEGIC.2010.5716876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel camera pose tracking system using a stochastic inertial-visual sensor fusion has been proposed. A method based on the Particle Filtering concept has been adapted for inertial and vision data fusion, which benefits from the agility of inertial-based tracking and robustness of vision-based camera tracking.\",\"PeriodicalId\":229345,\"journal\":{\"name\":\"2010 2nd International IEEE Consumer Electronics Society's Games Innovations Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International IEEE Consumer Electronics Society's Games Innovations Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEGIC.2010.5716876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International IEEE Consumer Electronics Society's Games Innovations Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEGIC.2010.5716876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A framework for camera pose tracking using stochastic data fusion
A novel camera pose tracking system using a stochastic inertial-visual sensor fusion has been proposed. A method based on the Particle Filtering concept has been adapted for inertial and vision data fusion, which benefits from the agility of inertial-based tracking and robustness of vision-based camera tracking.