Performance analysis of pedestrian detection at night time with different classifiers

Authors:
Praveen Cyriac;Philomina Simon
Affiliations:
Department of Computer Science, University of Kerala, India;Department of Computer Science, University of Kerala, India
Venue:
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
Year:
2011

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Abstract

Pedestrian detection is one of the most important components in driver-assistance system. A performance analysis is done with various classifiers (AdaBoost, Neural Network and SVM) and its behavior of the system is analyzed. As there is large intra-class variability in the pedestrian class, a two stage classifier is used. A review of different pedestrian detection system is done in the paper. Classifiers are arranged based on HAAR-like and HOG features in a coarse to fine manner. Adaboost gives better performance.