Mixture Models Based Background Subtraction for Video Surveillance Applications

Author(s):  
Chris Poppe ◽  
Gaëtan Martens ◽  
Peter Lambert ◽  
Rik Van de Walle
Sensors ◽  
2014 ◽  
Vol 14 (2) ◽  
pp. 1961-1987 ◽  
Author(s):  
Carlos del-Blanco ◽  
Tomás Mantecón ◽  
Massimo Camplani ◽  
Fernando Jaureguizar ◽  
Luis Salgado ◽  
...  

An object tracking increases loads of enthusiasm for dynamic research in applications such as video surveillance, vehicle navigation, highways, crowded public places, borders, forest and traffic monitoring areas. The system we develop aims to measure and analyze the application of background subtraction method and block matching algorithm to trace object movements through video-based. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection and tracking. This research applies background subtraction method to detect moving object, assisted with block matching algorithm which aims to get good results on objects that have been detected. Performance evaluation is carried out to determine the various parameters. In this paper author design and develop a novel algorithm for moving object tracking in video surveillance also compares and analyse existing algorithms for moving object tracking. Author main aim to design and develop an algorithm for moving object tracking to handle occlusion and complex object shapes.


2013 ◽  
Vol 74 (6) ◽  
pp. 1845-1862 ◽  
Author(s):  
Zhen Jia ◽  
Jianwei Zhao ◽  
Hongcheng Wang ◽  
Ziyou Xiong ◽  
Alan Finn

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