DocumentCode :
2822326
Title :
Algorithm Study for Pedestrian Detection Based on Monocular Vision
Author :
Lie, Guo ; Rong-ben, Wang ; Li-sheng, Jin ; Lin-hui, Li ; Lu, Yang
Author_Institution :
Jilin Univ., Changchun
fYear :
2006
fDate :
13-15 Dec. 2006
Firstpage :
83
Lastpage :
87
Abstract :
For intelligent vehicle and driving assistant system, pedestrian detection technology is an important research held to avoid dangerous traffic accidents. This article puts forward a pedestrian detection algorithm based on edge symmetry. First, lane recognition method is used to get area of interest (AOI) ahead of vehicle. Second, as pedestrian legs have prominent vertical edge symmetry, their symmetrical axis can be acquired through vertical edge extraction in the AOI. Combined with pedestrian transcendental features, the candidate pedestrian could be locked. Third, the candidate pedestrian will be validated based on the gray symmetry and local entropy. The experiment results show that the algorithm is effective, reliable and robust.
Keywords :
automated highways; computer vision; driver information systems; edge detection; road accidents; road traffic; road vehicles; dangerous traffic accident avoidance; driving assistant system; gray symmetry; intelligent vehicle; lane recognition method; local entropy; monocular vision; pedestrian detection algorithm; vertical edge extraction; Detection algorithms; Educational institutions; Entropy; Leg; Road accidents; Support vector machines; Transportation; Vehicle detection; Vehicle driving; Vehicles; Driver Assistance System; Machine Vision; Pedestrian Detection; Symmetry;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0759-1
Electronic_ISBN :
1-4244-0759-1
Type :
conf
DOI :
10.1109/ICVES.2006.371559
Filename :
4233995
Link To Document :
بازگشت