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
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;
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
DOI :
10.1109/SIU.2013.6531357