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Improved Real-time Implementation of Adaptive Gassian Mixture Model-based Object Detection Algorithm for Fixed-point DSP Processors  
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【英文篇名】 Improved Real-time Implementation of Adaptive Gassian Mixture Model-based Object Detection Algorithm for Fixed-point DSP Processors
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【作者】 Byung-eun LEE; Thanh-binh NGUYEN; Sun-tae CHUNG;
【英文作者】 Byung-eun LEE; Thanh-binh NGUYEN; Sun-tae CHUNG(School of Electronics Engineering; University of Soongsil; Seoul 156-743; Korea);
【作者单位】 School of Electronics Engineering; University of Soongsil; Seoul 156-743; Korea;
【文献出处】 Journal of Measurement Science and Instrumentation , 测试科学与仪器(英文版), 编辑部邮箱 2010年 02期  
期刊荣誉:ASPT来源刊  CJFD收录刊
【英文关键词】 background modeling; real-time computing; object detection;
【摘要】 Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance,HCI,object-based video compression,etc.One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model(AGMM).Although AGMM-based object detection shows very good performance with respect to object detection accuracy,AGMM is very complex model requiring lots of floating-point arithmetic so that it should pay for expensive computat...
【英文摘要】 Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance,HCI,object-based video compression,etc.One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model(AGMM).Although AGMM-based object detection shows very good performance with respect to object detection accuracy,AGMM is very complex model requiring lots of floating-point arithmetic so that it should pay for expensive computat...
【基金】 supported by Soongsil University Research Fund and BK 21 of Korea
【更新日期】 2013-12-12
【分类号】 TP368.1
【正文快照】 1IntroductionForeground moving object detection is an i mportantprocess in various computer vision applications such as in-telligent visual surveillance,HCI,object-basedvideocom-pression,etc.[1,8].Intelligent visual surveillance requiresanalyzinginteresti

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中国学术期刊网络出版总库
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