{"title":"基于dsp的增量直方图计算和粒子滤波跟踪算法及其实现","authors":"Xia Xuan, Liu Huaping, Xu Weiming, Sun Fuchun","doi":"10.1109/IVSURV.2011.6157026","DOIUrl":null,"url":null,"abstract":"Implementation of particle filter visual tracking on DSP platform will suffer from calculation bottleneck. To realize the real-time tracking, this paper uses the incremental histogram calculation algorithm to construct the histogram of color and edge orientation, integrates the histograms for the observation model and optimizes the target tracking algorithm on the DSP. The experiment proves that the algorithm is fast and the robustness of the system.","PeriodicalId":141829,"journal":{"name":"2011 Third Chinese Conference on Intelligent Visual Surveillance","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DSP-based incremental histogram calculation and particle filter tracking algorithm and its implementation\",\"authors\":\"Xia Xuan, Liu Huaping, Xu Weiming, Sun Fuchun\",\"doi\":\"10.1109/IVSURV.2011.6157026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Implementation of particle filter visual tracking on DSP platform will suffer from calculation bottleneck. To realize the real-time tracking, this paper uses the incremental histogram calculation algorithm to construct the histogram of color and edge orientation, integrates the histograms for the observation model and optimizes the target tracking algorithm on the DSP. The experiment proves that the algorithm is fast and the robustness of the system.\",\"PeriodicalId\":141829,\"journal\":{\"name\":\"2011 Third Chinese Conference on Intelligent Visual Surveillance\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Third Chinese Conference on Intelligent Visual Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVSURV.2011.6157026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third Chinese Conference on Intelligent Visual Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVSURV.2011.6157026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DSP-based incremental histogram calculation and particle filter tracking algorithm and its implementation
Implementation of particle filter visual tracking on DSP platform will suffer from calculation bottleneck. To realize the real-time tracking, this paper uses the incremental histogram calculation algorithm to construct the histogram of color and edge orientation, integrates the histograms for the observation model and optimizes the target tracking algorithm on the DSP. The experiment proves that the algorithm is fast and the robustness of the system.
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