Title :
Monocular vision-based range estimation of on-road vehicles
Author :
Chih-Ming Hsu ; Fei-Hong Chao ; Feng-Li Lian
Author_Institution :
Dept. of Mech. Eng., Nat. Taipei Univ. of Technol., Taipei, Taiwan
Abstract :
This paper presents a monocular vision-based range estimation of on-road vehicles approach. The proposed approach mainly combines non-drivable region from drivable region detection for detection region estimation instead of detecting the whole image, shadow detection for on-road object extraction, vehicle structure points estimation and adjusting for on-road vehicle classification, and motion vector and Kalman filter of on-road vehicles for collision avoiding. Extensive experimentation was performed to demonstrate that the proposed approach can correctly and dynamically estimate the relative distance of on-road vehicles in actual traffic conditions.
Keywords :
Kalman filters; collision avoidance; computer vision; feature extraction; image classification; image motion analysis; object detection; road vehicles; traffic engineering computing; Kalman filter; collision avoidance; drivable region detection; image detection; monocular vision-based range estimation; motion vector; nondrivable region detection; on-road object extraction; on-road vehicle classification; on-road vehicles approach; shadow detection; traffic conditions; vehicle structure points estimation; Artificial intelligence; Optical filters; Optical imaging; Roads; Vehicles;
Conference_Titel :
System Science and Engineering (ICSSE), 2014 IEEE International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/ICSSE.2014.6887912
