{"title":"A fast and energy efficient FPGA-based system for real-time object tracking","authors":"Xiaobai Chen, Jinlong Xu, Zhiyi Yu","doi":"10.1109/APSIPA.2017.8282162","DOIUrl":null,"url":null,"abstract":"Visual object tracking has achieved great advances in the past decades and has been widely applied in vision-based applications. Due to the popularization of the power-sensitive mobile platform, robust and low power real-time tracking solution is strongly required. An energy efficient real-time object tracking system on both static and moving camera is proposed in this paper. The system reduces the computational cost and explores data reuse by optimizing the tracking algorithm, the data flow, and the parallelism strategies. The architecture is implemented on a Xilinx ZC706 FPGA, and the experimental data shows that the system obtains 41 frame/s throughput for the 640×480 video and achieves higher energy efficiency comparing to other similar works.","PeriodicalId":142091,"journal":{"name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2017.8282162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Visual object tracking has achieved great advances in the past decades and has been widely applied in vision-based applications. Due to the popularization of the power-sensitive mobile platform, robust and low power real-time tracking solution is strongly required. An energy efficient real-time object tracking system on both static and moving camera is proposed in this paper. The system reduces the computational cost and explores data reuse by optimizing the tracking algorithm, the data flow, and the parallelism strategies. The architecture is implemented on a Xilinx ZC706 FPGA, and the experimental data shows that the system obtains 41 frame/s throughput for the 640×480 video and achieves higher energy efficiency comparing to other similar works.