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Vol. 177, Issue 8, August 2014, pp. 163-170

 

Bullet

 

Comprehensive Analysis and Evaluation of Background Subtraction Algorithms
for Surveillance Video
 

1 Yan Feng, 2, 3 Shengmei Luo, 1 Yumin Tian, 2 Shuo Deng, 1 Haihong Zheng

1 School of Computer Science, Xidian University, Xi’an, 710071, China
2 Zhongxing Telecommunication Equipment Corporation, Nanjing, 210012, China
3 Department of Science and technology, Tsinghua University, Beijing, 100084, China
1 Tel.: 13468654755

1 E-mail: fysmile606@163.com

 

Received: 2 July 2014 /Accepted: 4 August 2014 /Published: 31 August 2014

Digital Sensors and Sensor Sysstems

 

Abstract: Background Subtraction techniques are the basis for moving target detection and tracking in the domain of video surveillance, while the robust and reliable detection and tracking algorithms in complex environment is a challenging subject, so evaluations of various background subtraction algorithms are of great significance. Nine state of the art methods ranging from simple to sophisticated ones are discussed. Then the algorithms were implemented and tested using different videos with ground truth, such as baseline, dynamic background, camera jitter, and intermittent object motion and shadow scenarios. The best suited background modeling methods for each scenario are given by comprehensive analysis of three parameters: recall, precision and F-Measure, which facilitates more accurate target detection and tracking.

 

Keywords: Surveillance video, Background modeling, Motion scenario, Performance evaluation.

 

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