Title :
On addressing driving inattentiveness: Robust rear light status classification using Hierarchical Matching Pursuit
Author :
Zhiyong Cui ; Shao-Wen Yang ; Chenqi Wang ; Hsin-Mu Tsai
Author_Institution :
Dept. of Software & Microelectron., Peking Univ., Beijing, China
Abstract :
Automatically recognizing rear light signals of front vehicles can significantly improve driving safety by automatic alarm and taking actions proactively to prevent collisions and accidents. Much previous research only focuses on the detection of brake signals at night. In this paper, we propose a novel and robust framework to detect rear lights of vehicles and estimate their signal states at daytime. Comparing with existing state-of-the-art works, our experimental results show the high detection rate and robustness of our system in complicated light conditions.
Keywords :
image classification; image matching; object detection; object recognition; traffic engineering computing; brake signal detection; driving inattentiveness; driving safety; hierarchical matching pursuit; light conditions; rear light signal recognition; rear light status classification; signal state estimation; Accuracy; Image color analysis; Matching pursuit algorithms; Optics; Robustness; Turning; Vehicles;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ITSC.2014.6958037