{"title":"Multiple 3D Object tracking for augmented reality","authors":"Youngmin Park, V. Lepetit, Woontack Woo","doi":"10.1109/ISMAR.2008.4637336","DOIUrl":null,"url":null,"abstract":"We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real-time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: Frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches, and demonstrate our method on several real sequences.","PeriodicalId":168134,"journal":{"name":"2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"135","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMAR.2008.4637336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 135
Abstract
We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real-time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: Frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches, and demonstrate our method on several real sequences.