Marius Tennøe, Espen Helgedagsrud, Mikkel Næss, Henrik Kjus Alstad, H. Stensland, V. Reddy, Dag Johansen, C. Griwodz, P. Halvorsen
{"title":"Efficient Implementation and Processing of a Real-Time Panorama Video Pipeline","authors":"Marius Tennøe, Espen Helgedagsrud, Mikkel Næss, Henrik Kjus Alstad, H. Stensland, V. Reddy, Dag Johansen, C. Griwodz, P. Halvorsen","doi":"10.1109/ISM.2013.21","DOIUrl":null,"url":null,"abstract":"High resolution, wide field of view video generated from multiple camera feeds has many use cases. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent requirements of timeliness. We use panorama video in a sport analysis system where video events must be generated in real-time. In this respect, we present a system for real-time panorama video generation from an array of low-cost CCD HD video cameras. We describe how we have implemented different components and evaluated alternatives. We also present performance results with and without co-processors like graphics processing units (GPUs), and we evaluate each individual component and show how the entire pipeline is able to run in real-time on commodity hardware.","PeriodicalId":6311,"journal":{"name":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","volume":"131 1","pages":"76-83"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2013.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
High resolution, wide field of view video generated from multiple camera feeds has many use cases. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent requirements of timeliness. We use panorama video in a sport analysis system where video events must be generated in real-time. In this respect, we present a system for real-time panorama video generation from an array of low-cost CCD HD video cameras. We describe how we have implemented different components and evaluated alternatives. We also present performance results with and without co-processors like graphics processing units (GPUs), and we evaluate each individual component and show how the entire pipeline is able to run in real-time on commodity hardware.