{"title":"实时二维稳像的SIMD、SMP和MIMD-DM并行方法","authors":"J. Derutin, Fabio Dias, L. Damez, N. Allezard","doi":"10.1109/CAMP.2005.48","DOIUrl":null,"url":null,"abstract":"We present a real-time image stabilization method, based on a 2D motion model and different levels of parallel implementation. This stabilization method is decomposed into three main parts. First, the image matching is determined by a feature-based technique, then the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. This component is finally used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some of the results, concerning the parallel implementation of the algorithm, using the MW ALTIVEC/spl reg/ instructions set, a symmetric multi-processor (SMP) architecture and MIMD-DM architecture.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"SIMD, SMP and MIMD-DM parallel approaches for real-time 2D image stabilization\",\"authors\":\"J. Derutin, Fabio Dias, L. Damez, N. Allezard\",\"doi\":\"10.1109/CAMP.2005.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a real-time image stabilization method, based on a 2D motion model and different levels of parallel implementation. This stabilization method is decomposed into three main parts. First, the image matching is determined by a feature-based technique, then the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. This component is finally used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some of the results, concerning the parallel implementation of the algorithm, using the MW ALTIVEC/spl reg/ instructions set, a symmetric multi-processor (SMP) architecture and MIMD-DM architecture.\",\"PeriodicalId\":393875,\"journal\":{\"name\":\"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMP.2005.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMP.2005.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SIMD, SMP and MIMD-DM parallel approaches for real-time 2D image stabilization
We present a real-time image stabilization method, based on a 2D motion model and different levels of parallel implementation. This stabilization method is decomposed into three main parts. First, the image matching is determined by a feature-based technique, then the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. This component is finally used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some of the results, concerning the parallel implementation of the algorithm, using the MW ALTIVEC/spl reg/ instructions set, a symmetric multi-processor (SMP) architecture and MIMD-DM architecture.