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
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;
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
DOI :
10.1109/ICVES.2007.4456404
