Motion detectio n based on background modeling and performance analysis for outdoor surveillance

Tianci Huang, Jingbang Qiu, Takahiro Sakayori, Satoshi Goto, Takeshi Ikenaga

研究成果: Conference contribution

13 被引用数 (Scopus)

抄録

Real-time segmentation of moving objects in video sequences is a fundamental step for surveillance systems. One of successful methods for complex background is to use a multi-color background model per pixel. However, Common problem for this approach is that it suffers from illumination changing environment, in addition, it is incapable of removing shadows of moving objects. This paper proposed an effective scheme to improve the adaptive background model for each pixel by introducing a background training parameter into every Gaussian model, and region-based scheme is applied to judgment by utilizing both spatial and temporal information. Experimental results will be presented to validate proposed algorithm keep robustness in the situation of illumination changes, shadow can be removed in foreground mask, results shows False Alarm Rate can be reduced from 34.9% to 35.8% while the overlap varies within normal range from 0.4 to 0.6 compared with conventional Gaussian mixture model.

本文言語English
ホスト出版物のタイトルProceedings - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009
ページ38-42
ページ数5
DOI
出版ステータスPublished - 2009 4 23
イベント2009 International Conference on Computer Modeling and Simulation, ICCMS 2009 - Macau, China
継続期間: 2009 2 202009 2 22

出版物シリーズ

名前Proceedings - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009

Conference

Conference2009 International Conference on Computer Modeling and Simulation, ICCMS 2009
CountryChina
CityMacau
Period09/2/2009/2/22

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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