S. Liu, Alexandros Papakonstantinou, Hongjun Wang, Deming Chen
{"title":"Real-Time Object Tracking System on FPGAs","authors":"S. Liu, Alexandros Papakonstantinou, Hongjun Wang, Deming Chen","doi":"10.1109/SAAHPC.2011.22","DOIUrl":null,"url":null,"abstract":"Object tracking is an important task in computer vision applications. One of the crucial challenges is the real-time speed requirement. In this paper we implement an object tracking system in reconfigurable hardware using an efficient parallel architecture. In our implementation, we adopt a background subtraction based algorithm. The designed object tracker exploits hardware parallelism to achieve high system speed. We also propose a dual object region search technique to further boost the performance of our system under complex tracking conditions. For our hardware implementation we use the Alter a Stratix III EP3SL340H1152C2 FPGA device. We compare the proposed FPGA-based implementation with the software implementation running on a 2.2 GHz processor. The observed speedup can reach more than 100X for complex video inputs.","PeriodicalId":331604,"journal":{"name":"2011 Symposium on Application Accelerators in High-Performance Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Symposium on Application Accelerators in High-Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAAHPC.2011.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
Abstract
Object tracking is an important task in computer vision applications. One of the crucial challenges is the real-time speed requirement. In this paper we implement an object tracking system in reconfigurable hardware using an efficient parallel architecture. In our implementation, we adopt a background subtraction based algorithm. The designed object tracker exploits hardware parallelism to achieve high system speed. We also propose a dual object region search technique to further boost the performance of our system under complex tracking conditions. For our hardware implementation we use the Alter a Stratix III EP3SL340H1152C2 FPGA device. We compare the proposed FPGA-based implementation with the software implementation running on a 2.2 GHz processor. The observed speedup can reach more than 100X for complex video inputs.