A foreground extraction algorithm based on adaptively adjusted gaussian mixture models

Tianci Huang, Jing Bang Qiu, Takeshi Ikenaga

研究成果: Conference contribution

8 引用 (Scopus)

抜粋

Background subtraction is a widely used method for moving object detection in computer vision field. To cope with highly dynamic and complex environments, the mixture of models has been proposed. In this paper, a background subtraction method is proposed based on the popular Gaussian Mixture Models technique and a scheme is put forward to adaptively adjust the number of Gaussian distributions aiming at speeding up execution. Moreover, edge-based image is utilized to weaken the effect of illumination changes and shadows of moving objects. The final foreground mask is extracted by the proposed data fusion scheme. Experimental results validate the performance of proposed algorithm in both computational complexity and segmentation quality.

元の言語English
ホスト出版物のタイトルNCM 2009 - 5th International Joint Conference on INC, IMS, and IDC
ページ1662-1667
ページ数6
DOI
出版物ステータスPublished - 2009 12 1
イベントNCM 2009 - 5th International Joint Conference on Int. Conf. on Networked Computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications - Seoul, Korea, Republic of
継続期間: 2009 8 252009 8 27

出版物シリーズ

名前NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC

Conference

ConferenceNCM 2009 - 5th International Joint Conference on Int. Conf. on Networked Computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications
Korea, Republic of
Seoul
期間09/8/2509/8/27

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Software

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  • これを引用

    Huang, T., Qiu, J. B., & Ikenaga, T. (2009). A foreground extraction algorithm based on adaptively adjusted gaussian mixture models. : NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC (pp. 1662-1667). [5331586] (NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC). https://doi.org/10.1109/NCM.2009.40