Mixture Models Based Background Subtraction for Video Surveillance Applications

2007 ◽  
pp. 28-35 ◽  
Author(s):  
Chris Poppe ◽  
Gaëtan Martens ◽  
Peter Lambert ◽  
Rik Van de Walle
Keyword(s):  
Mixture Models ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Surveillance Applications

Improved Background Mixture Models for Video Surveillance Applications

2007 ◽  
pp. 251-260 ◽  
Author(s):  
Chris Poppe ◽  
Gaëtan Martens ◽  
Peter Lambert ◽  
Rik Van de Walle
Keyword(s):  
Mixture Models ◽  
Video Surveillance ◽  
Surveillance Applications

scholarly journals Foreground Segmentation in Depth Imagery Using Depth and Spatial Dynamic Models for Video Surveillance Applications

Sensors ◽  
2014 ◽  
Vol 14 (2) ◽  
pp. 1961-1987 ◽  
Author(s):  
Carlos del-Blanco ◽  
Tomás Mantecón ◽  
Massimo Camplani ◽  
Fernando Jaureguizar ◽  
Luis Salgado ◽  
...  
Keyword(s):  
Video Surveillance ◽  
Dynamic Models ◽  
Foreground Segmentation ◽  
Spatial Dynamic ◽  
Surveillance Applications

scholarly journals Moving Object Tracking Algorithm for Complex Shape and Occlusion Handling

2019 ◽  
Vol 9 (1) ◽  
pp. 6299-6304
Keyword(s):  
Object Tracking ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Traffic Monitoring ◽  
Block Matching ◽  
Moving Object ◽  
Subtraction Method ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Moving Object Tracking

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.

A two-step face hallucination approach for video surveillance applications

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