Omnidirectional stereo vision based vehicle detection and distance measurement for driver assistance system

Author(s):  
Donguk Seo ◽  
Hansung Park ◽  
Kanghyun Jo ◽  
Kangik Eom ◽  
Sungmin Yang ◽  
...  
2014 ◽  
Vol 678 ◽  
pp. 35-38 ◽  
Author(s):  
Peng He ◽  
Feng Gao

Perception of environment in front of driving vehicle is a core investigation theme of intelligent vehicle technologies aiming to increase safety, convenience and efficiency of driving. Using stereo vision for environment perception is a hot technology. This paper developed an algorithm for stereo matching in intelligent vehicle application. The experimental results indicate that this algorithm is effective. Furthermore, this algorithm paves the way for the implementation of automotive driver assistance system.


2014 ◽  
Vol 687-691 ◽  
pp. 3884-3888
Author(s):  
Xing Xing He ◽  
Lei Ding ◽  
Ping Wang ◽  
Fu Qiang Liu ◽  
Xin Hong Wang

Apply driving assistance system to vehicles can significantly reduce accidences and thus attracts much interest nowadays. However, most existing systems are designed specifically for small vehicles and always suffer from drawbacks such as low pedestrian and vehicle detection accuracy and long detection time. To solve these issues, in this paper we develop a driver assistance system based on radar and camera, which can be applied to large vehicles and can detect vehicle and pedestrian simultaneously. Specifically, we combine the image subtraction technique and histogram algorithm to perform pedestrian and vehicle detection to improve detection rate. What’s more, this system can automatically determine whether the object is inside a danger region. If yes, an associated warning signal will be triggered to alarm the driver. Experimental results show that the successful detection rate is sufficiently good and the detecting speed is fast enough to timely alarm the driver to avoid accidents.


2015 ◽  
Vol 22 (2) ◽  
pp. 197-209 ◽  
Author(s):  
Qin Gu ◽  
Jianyu Yang ◽  
Yuqiang Zhai ◽  
Lingjiang Kong

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