DocumentCode :
237601
Title :
Background modelling, detection and tracking of human in video surveillance system
Author :
Kaur, Rupinderjit ; Singh, Sushil
Author_Institution :
Discipline of ECE, Lovely Prof. Univ., Phagwara, India
fYear :
2014
fDate :
28-29 Nov. 2014
Firstpage :
54
Lastpage :
58
Abstract :
Video Surveillance System is a powerful tool used for monitoring people and their activities for public security. The motive of having surveillance system is not only to put cameras in place of human eyes, but also making it capable for recognizing activities automatically. In this paper, human detection and tracking is performed on Weizmann dataset having various activities like run, bend, hand wave, skip, etc. First background modelling is done by taking mean of first n frames. After this, human detection is done using background subtraction algorithm and then tracking is done using Kalman filter. Result of each stage has been discussed. The proposed methodology shows promising results which can further be used for activity recognition.
Keywords :
Kalman filters; object detection; object tracking; security; video surveillance; Kalman filter; Weizmann dataset; activity recognition; background modelling; background subtraction algorithm; human detection; human tracking; people monitoring; public security; video surveillance system; Cameras; Feature extraction; Kalman filters; Mathematical model; Video surveillance; Background subtraction; Gaussian Mixture Model; Kalman filter; Video surveillance systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 2014 Innovative Applications of
Conference_Location :
Ghaziabad
Type :
conf
DOI :
10.1109/CIPECH.2014.7019097
Filename :
7019097
Link To Document :
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