DocumentCode
3052960
Title
Vision-based real-time pedestrian detection for autonomous vehicle
Author
Xin, Liu ; Bin, Dai ; Hangen, He
Author_Institution
Nat. Univ. of Defense Technol., Changsha
fYear
2007
fDate
13-15 Dec. 2007
Firstpage
1
Lastpage
5
Abstract
TMs paper presents a real-time single-frame pedestrian detection approach. Combining efficient interesting regions selection and proper SVM classifier, the method is applicable to the autonomous vehicles running on urban roads. Experiment results with test dataset extracted from real driving on urban roads are presented to illustrate the performance of this approach.
Keywords
computer vision; image resolution; object detection; road vehicles; support vector machines; traffic engineering computing; SVM classifier; autonomous road vehicle; image resolution; vision-based real-time pedestrian detection; Cameras; Image resolution; Mobile robots; Remotely operated vehicles; Road safety; Road vehicles; Support vector machine classification; Support vector machines; Vehicle detection; Vehicle safety;
fLanguage
English
Publisher
ieee
Conference_Titel
Vehicular Electronics and Safety, 2007. ICVES. IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-1265-5
Electronic_ISBN
978-1-4244-1266-2
Type
conf
DOI
10.1109/ICVES.2007.4456404
Filename
4456404
Link To Document