Architecture design for a low-cost and low-complexity foreground object segmentation with multi-model background maintenance algorithm

De Zhang Peng, Chung Yuan Lin, Wen Tsai Sheu, Tsung Han Tsai

研究成果: 書貢獻/報告類型會議論文篇章同行評審

7 引文 斯高帕斯(Scopus)

摘要

This paper presents an architecture design for a low cost and low complexity foreground object detection based on Multi-model Background Maintenance (MBM) algorithm [1]. The MBM framework basically contains two principal features. These features consist of static and dynamic pixels to represent the characteristic of background. Under this framework, a pure time-varying background image is maintained and learned using the statistical information of the multiple Gaussian distribution with principal features. In the MBM architecture, look-up table based Gaussian density function architecture is proposed. Three look-up tables are used for exponential and division of the Gaussian density function. The characteristic of Gaussian density function is also used to enormously reduce the table size in a low cost and low complexity consideration. The total gate count of the foreground object detection architecture is about 14.4K gates with TSMC 0.18 um technology. The operation frequency of this design is up to 100MHz.

原文???core.languages.en_GB???
主出版物標題2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
發行者IEEE Computer Society
頁面3241-3244
頁數4
ISBN(列印)9781424456543
DOIs
出版狀態已出版 - 2009
事件2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
持續時間: 7 11月 200910 11月 2009

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
ISSN(列印)1522-4880

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???event.eventtypes.event.conference???2009 IEEE International Conference on Image Processing, ICIP 2009
國家/地區Egypt
城市Cairo
期間7/11/0910/11/09

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