An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Modeling background and segmenting moving objects are significant techniques for computer vision applications.
Mixture-of-Gaussians (MoG) background model is commonly used in foreground extraction in video steam.
However considering the case that the objects enter the scenery and stay for a while, the foreground extraction would fail as the objects stay still and gradually merge into the background.
In this paper, we adopt a blob tracking method to cope with this situation.
To construct the MoG model more quickly, we add frame difference method to the foreground extracted from MoG for very crowded situations.
What is more, a new shadow removal method based on RGB color space is proposed.
American Psychological Association (APA)
Yao, Li& Ling, Miaogen. 2014. An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049582
Modern Language Association (MLA)
Yao, Li& Ling, Miaogen. An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1049582
American Medical Association (AMA)
Yao, Li& Ling, Miaogen. An Improved Mixture-of-Gaussians Background Model with Frame Difference and Blob Tracking in Video Stream. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049582
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049582
