Vehicle Detection Counting Algorithm Based on Background Subtraction Algorithm and SORT

Author(s):  
Jun Guo ◽  
Heyan Gao ◽  
Zeyu Yan ◽  
Jiahui Cao ◽  
Zhenbo Fu
2014 ◽  
Vol 644-650 ◽  
pp. 930-933 ◽  
Author(s):  
Yan Li Luo ◽  
Han Lin Wan ◽  
Li Xia Xue ◽  
Qing Bin Gao

This paper proposes an adaptive moving vehicle detection algorithm based on hybrid background subtraction and frame difference. The background image of continuous video frequency is reconstructed by calculating the maximun probability grayscale using grey histogram; Moving regions is gained by frame defference, the initial target image is obtained by background difference method,moving regions image and initial target image AND,XOR and OR operations to get the vehicle moving target images. Experimental results show that the algorithm can response timely to the actual scene changes and improve the quality of moving vehicle detection.


2014 ◽  
Vol 602-605 ◽  
pp. 2362-2365
Author(s):  
Quan Wu Li ◽  
Yu Hui Li ◽  
Bo Li ◽  
Yi Chen

Focused on static high-definition sequence images captured on the highway bayonet, this paper proposes a new approach for vehicle detection and shadow elimination based on average background modeling, which uses average background model and background subtraction to locate vehicle roughly, eliminates shadow of the vehicle using canny edge detection with dynamic histogram threshold determined by the histogram of the image. Experiments show that this method can locate the position of vehicle quickly and accurately.


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