{"title":"一种用于卡尔曼滤波的异构M-SIMD结构控制了图像序列的处理","authors":"G. Nudd, T. Atherton, D. Kerbyson","doi":"10.1109/CVPR.1992.223243","DOIUrl":null,"url":null,"abstract":"The use of a heterogeneous multiple-SIMD (M-SIMD) architecture with image-based measurements and optimal (Kalman) estimators for the analysis of image sequences is illustrated. The architecture integrates SIMD and MIMD processing paradigms, combining heterogeneity of processor types matched to the computation at each level and operational autonomy within an SIMD array. It is suited to real-time simultaneous data parallel (iconic) and control parallel (numeric) processing.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An heterogeneous M-SIMD architecture for Kalman filter controlled processing of image sequences\",\"authors\":\"G. Nudd, T. Atherton, D. Kerbyson\",\"doi\":\"10.1109/CVPR.1992.223243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of a heterogeneous multiple-SIMD (M-SIMD) architecture with image-based measurements and optimal (Kalman) estimators for the analysis of image sequences is illustrated. The architecture integrates SIMD and MIMD processing paradigms, combining heterogeneity of processor types matched to the computation at each level and operational autonomy within an SIMD array. It is suited to real-time simultaneous data parallel (iconic) and control parallel (numeric) processing.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1992.223243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An heterogeneous M-SIMD architecture for Kalman filter controlled processing of image sequences
The use of a heterogeneous multiple-SIMD (M-SIMD) architecture with image-based measurements and optimal (Kalman) estimators for the analysis of image sequences is illustrated. The architecture integrates SIMD and MIMD processing paradigms, combining heterogeneity of processor types matched to the computation at each level and operational autonomy within an SIMD array. It is suited to real-time simultaneous data parallel (iconic) and control parallel (numeric) processing.<>
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