DocumentCode :
265998
Title :
Parallelepipedic shape modeling for moving objects in video surveillance systems
Author :
Ben Hamida, Ahmed ; Koubaa, Mohamed ; Ben Amar, Chokri ; Nicolas, H.
Author_Institution :
REGIM-Lab.: Res. Groups in Intell. Machines, Univ. of Sfax, Sfax, Tunisia
fYear :
2014
fDate :
27-29 Aug. 2014
Firstpage :
379
Lastpage :
383
Abstract :
The major challenge of video surveillance systems is the automated detection and interpretation of events of interest. In case of an abnormal event taking place, an alert should be delivered. Generally, a video surveillance system´s framework combines three main phases: moving objects extraction, moving objects classification and tracking, scenario recognition. The last stage depends on the aimed application such as moving objects counting or moving objects behavior understanding. The extraction of moving objects, followed by the object tracking and recognition, are very crucial stages that affect the whole subsequent process. In this paper, we propose a geometric 3D shape modeling method to represent the moving object in a parallelepiped shape aiming to simplify the object representation. At the same time, the required features for objects tracking are maintained. Experimental results are given to demonstrate that the proposed technique is effective and efficient for road traffic surveillance.
Keywords :
feature extraction; image classification; image motion analysis; object detection; object recognition; object tracking; road traffic; solid modelling; video surveillance; automated event detection; event interpretation; geometric 3D shape modeling method; moving object classification; moving object counting; moving object extraction; moving object tracking; moving objects behavior understanding; object recognition; object representation; parallelepipedic shape modeling; road traffic surveillance; scenario recognition; video surveillance systems; Cameras; Computational modeling; Conferences; Shape; Solid modeling; Three-dimensional displays; Video surveillance; 3D shape model; object detection; object tracking; video surveillance system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Science and Information Conference (SAI), 2014
Conference_Location :
London
Print_ISBN :
978-0-9893-1933-1
Type :
conf
DOI :
10.1109/SAI.2014.6918214
Filename :
6918214
Link To Document :
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