Title :
Real-time rear of vehicle detection from a moving camera
Author :
Qing Xu ; Feng Gao ; Ke Shi ; Guoyan Xu
Author_Institution :
Sch. of Transp. Sci. & Eng., Beihang Univ., Beijing, China
fDate :
May 31 2014-June 2 2014
Abstract :
Based on the requirement of real-time on road vehicle detection from a moving camera, a feature based rear of vehicle detection algorithm is developed. A Haar-like feature classifier is trained to capture the rear of vehicles from the video stream in real-time and a premier test is performed. Aiming at some issues found in the test, which include duplicated detection, false alarms, undetected objects and the failure of detecting distant object due to limited resolution, a revised algorithm is given. Some further tests and analyses indicate that the revised algorithm can effectively detect the rear of vehicles in real-time with complex background from a moving camera.
Keywords :
Haar transforms; cameras; image resolution; object detection; real-time systems; road vehicles; video streaming; Haar-like feature; distant object detection failure; duplicated detection; false alarms; limited resolution; moving camera; premier test; real-time rear; road vehicle detection algorithm; undetected objects; video stream; Cameras; Feature extraction; Real-time systems; Road vehicles; Training; Vehicle detection; Haar-like feature; Vehicle detection; Vision sensing;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852989