{"title":"一种实时应用的horn - schunck光流算法的fpga优化架构","authors":"Michael Kunz, Alexander Ostrowski, P. Zipf","doi":"10.1109/FPL.2014.6927406","DOIUrl":null,"url":null,"abstract":"Optical flow estimation of image sequences is one of the key elements for motion detection. However, processing the optical flow in real-time is still an open task due to its computationally expensive nature. In this paper we present an FPGA-optimized architecture for optical flow estimation based on the algorithm of Horn and Schunck. While existing FPGA-realizations are only partly real-time capable, on a Stratix IV our architecture enables the computation of the optical flow for each pixel of a frame with 640 × 512 pixels at a framerate of 30 fps in iterative and up to 4k resolution (4,096 × 2,304 pixels) at a framerate of 20 fps in full-pipelined form.","PeriodicalId":172795,"journal":{"name":"2014 24th International Conference on Field Programmable Logic and Applications (FPL)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"An FPGA-optimized architecture of horn and schunck optical flow algorithm for real-time applications\",\"authors\":\"Michael Kunz, Alexander Ostrowski, P. Zipf\",\"doi\":\"10.1109/FPL.2014.6927406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optical flow estimation of image sequences is one of the key elements for motion detection. However, processing the optical flow in real-time is still an open task due to its computationally expensive nature. In this paper we present an FPGA-optimized architecture for optical flow estimation based on the algorithm of Horn and Schunck. While existing FPGA-realizations are only partly real-time capable, on a Stratix IV our architecture enables the computation of the optical flow for each pixel of a frame with 640 × 512 pixels at a framerate of 30 fps in iterative and up to 4k resolution (4,096 × 2,304 pixels) at a framerate of 20 fps in full-pipelined form.\",\"PeriodicalId\":172795,\"journal\":{\"name\":\"2014 24th International Conference on Field Programmable Logic and Applications (FPL)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 24th International Conference on Field Programmable Logic and Applications (FPL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPL.2014.6927406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 24th International Conference on Field Programmable Logic and Applications (FPL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPL.2014.6927406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An FPGA-optimized architecture of horn and schunck optical flow algorithm for real-time applications
Optical flow estimation of image sequences is one of the key elements for motion detection. However, processing the optical flow in real-time is still an open task due to its computationally expensive nature. In this paper we present an FPGA-optimized architecture for optical flow estimation based on the algorithm of Horn and Schunck. While existing FPGA-realizations are only partly real-time capable, on a Stratix IV our architecture enables the computation of the optical flow for each pixel of a frame with 640 × 512 pixels at a framerate of 30 fps in iterative and up to 4k resolution (4,096 × 2,304 pixels) at a framerate of 20 fps in full-pipelined form.