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Compressive Background Modeling for Foreground Extraction
Joint Authors
Lu, Qian
Wang, Dianhong
Liu, Wei
Wang, Yong
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-16
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Robust and efficient foreground extraction is a crucial topic in many computer vision applications.
In this paper, we propose an accurate and computationally efficient background subtraction method.
The key idea is to reduce the data dimensionality of image frame based on compressive sensing and in the meanwhile apply sparse representation to build the current background by a set of preceding background images.
According to greedy iterative optimization, the background image and background subtracted image can be recovered by using a few compressive measurements.
The proposed method is validated through multiple challenging video sequences.
Experimental results demonstrate the fact that the performance of our approach is comparable to those of existing classical background subtraction techniques.
American Psychological Association (APA)
Wang, Yong& Lu, Qian& Wang, Dianhong& Liu, Wei. 2015. Compressive Background Modeling for Foreground Extraction. Journal of Electrical and Computer Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1068094
Modern Language Association (MLA)
Wang, Yong…[et al.]. Compressive Background Modeling for Foreground Extraction. Journal of Electrical and Computer Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1068094
American Medical Association (AMA)
Wang, Yong& Lu, Qian& Wang, Dianhong& Liu, Wei. Compressive Background Modeling for Foreground Extraction. Journal of Electrical and Computer Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1068094
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1068094