Paper Info
Title
Gestalt Principle Based Change Detection and Background Reconstruction.
Abstract
Gaussian mixture model based detection algorithms can easily lead to fragmentary due to the fixed number of Gaussian components. In this paper, we propose a gestalt principle based change target extraction method, and further present a background reconstruction algorithm. In particular, firstly we applied the Gaussian mixture model to extract the moving target as others did but this may lead to incomplete extraction. Secondly, we have also tried to apply the frame difference method to extract the moving target more precisely. Finally, we determine to build a static background according to relationships between each frame of a moving target. Experiment results reveal that the proposed detection method outperforms the other three representative detection methods. Moreover, our background reconstruction algorithm is also proved to be very effective and robust in reconstructing the backgrounds of a video.
Year
DOI
Venue
2016
10.1007/978-981-10-3476-3_3
Communications in Computer and Information Science
Keywords
Field
DocType
Gestalt visual principle,Moving target extraction,Background reconstruction,Video surveillance
Computer vision,Change detection,Computer science,Frame difference,Gestalt psychology,Reconstruction algorithm,Gaussian,Artificial intelligence,Mixture model
Conference
Volume
ISSN
Citations 
664
1865-0929
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Shi Qiu125029.03
Yongsheng Dong223017.59
Xiaoqiang Lu3119174.48
Ming Du400.34