Title
Real-Time Automatic Obstacle Detection method for Traffic Surveillance in Urban Traffic
Abstract
Obstacle detection in urban traffic is a hot topic in intelligent visual surveillance systems. In this paper, a real-time automatic obstacle recognition method based on computer vision technology is presented. The proposed method aims at detecting and recognizing the road obstacles such as abandoned objects, accident vehicles and illegally parked vehicles, which can prevent the traffic accident effectively. In the method, the target images are captured by a visible image sensor firstly. In order to avoid the static objects disappearing from foreground in short time when using GMM (Gaussian Mixture Model), background is built and foreground objects are extracted by the proposed algorithm SUOG (Selective Updating of GMM). Relative object speed is used to detect the static obstacles, and FROI (Flushed Region of Interest) algorithm based on the concept of connected domain, is presented to eliminate noises outside road and improve real-time capability. At last, a classification method of adaptive interested region based on HOG and SVM, and a new recognition algorithm of accident vehicles based on multi-feature fusion are proposed to classify the road obstacles. Experiments indicate that the detection rate of the proposed obstacle detection method is up to 96 % in urban road traffic. Through experiment, it is shown that the developed obstacle detection method has low computational complexity, and can fulfill the requirement of real-time applications, and it is correct and effective.
Year
DOI
Venue
2016
10.1007/s11265-015-1006-4
Journal of Signal Processing Systems
Keywords
Field
DocType
Video surveillance,Feature extraction,SVM,Obstacle detection
Obstacle,Computer vision,Image sensor,Computer science,Support vector machine,Feature extraction,Real-time computing,Artificial intelligence,Recognition algorithm,Region of interest,Mixture model,Computational complexity theory
Journal
Volume
Issue
ISSN
82
3
1939-8018
Citations 
PageRank 
References 
7
0.46
17
Authors
5
Name
Order
Citations
PageRank
Jinhui Lan1216.55
yaoliang jiang270.80
Guoliang Fan377579.20
D. Yu471.82
Qi Zhang5121.43