Title :
A Fast Method for Building and Updating Background Model
Author :
Zhu, Juan ; Kong, YongPing
Author_Institution :
Dept. of Comput. Applic., South China Univ. of Technol., Guangzhou
Abstract :
On the basic of the video traffic surveillance system, the Vehicle detection is a crucial step. A typical method is background subtraction. Extracting and updating the background plays an important role on speed and efficiency of detection. For this reason, the author puts forward a fast and effective method for building and updating the background model. First, adopt the improved statistical method to build initial background. Second, get the vista of the picture per frame by means of background subtraction, and bring forward the background updating method based on the container technology. Finally, in its updating stage, use the pixel excluding the pixel in vista region to renew the background model. The data of experimental picture states clearly that competed with the traditional method, detection technology is robust and accurate. Furthermore, on the realization of arithmetic, it is easier to operate and it has higher timeliness.
Keywords :
computer vision; object detection; road traffic; road vehicles; statistical analysis; surveillance; traffic engineering computing; video signal processing; background model building; background model updating; background subtraction; container technology; statistical method; vehicle detection; video traffic surveillance system; vista region; Arithmetic; Cameras; Computer applications; Computer science; Intelligent transportation systems; Roads; Robust stability; Statistical analysis; Traffic control; Vehicle detection;
Conference_Titel :
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3893-8
Electronic_ISBN :
978-1-4244-3894-5
DOI :
10.1109/IWISA.2009.5072618