DocumentCode :
607696
Title :
A pedestrian detection system with weak classifiers
Author :
Tetik, Y.E. ; Bolat, B.
Author_Institution :
Multimedya Sinyal Analiz Laboratuari, Yildiz Teknik Univ., İstanbul, Turkey
fYear :
2013
fDate :
24-26 April 2013
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, a pedestrian detection system which uses sliding window approach to detect pedestrians in still digital images is presented. The proposed pedestrian detection system combines weak classifiers in an Adaboost like novel way to create a strong classifier. Besides, rectangle ratios and discrete cosine transform coefficients are used as features with the well-known rectangle differences method.
Keywords :
discrete cosine transforms; image classification; object detection; pedestrians; digital image; discrete cosine transform coefficient; pedestrian detection system; rectangle difference method; rectangle ratio; sliding window; weak classifier; Abstracts; Boosting; Computer vision; Computers; Conferences; Digital images; Pattern recognition; adaboost; pedestrian detection system; rectangle differences; rectangle ratios; sliding window approach; weak classifiers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
Type :
conf
DOI :
10.1109/SIU.2013.6531357
Filename :
6531357
Link To Document :
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