Vision based pedestrian detection using Histogram of Oriented Gradients, Adaboost & Linear Support Vector Machines

Author

Hilado, Samantha D. F. ; Dadios, Elmer P. ; Gan Lim, Laurence A. ; Sybingco, Edwin ; Marfori, I.V. ; Chua, A.Y.

Author_Institution

Mech. Eng´g Dept., De La Salle Univ., Manila, Philippines

fYear

2012

fDate

19-22 Nov. 2012

Firstpage

1

Lastpage

5

Abstract

Pedestrian detection systems are valuable in a variety of applications such as in advanced driver assistance systems and advanced robots. This study presents a pedestrian detection system that uses Histogram of Oriented Gradients (HOG) as feature descriptor, and AdaBoost and Linear Support Vector Machines (SVM) as classifiers. The entire system is tested and evaluated in both publicly available databases and personally acquired videos. The pedestrian detection system has been tested and results show that it can detect pedestrians. Experiments showed that the system is up 20% faster compared to OpenCV´s default detector.

Keywords

driver information systems; feature extraction; image classification; learning (artificial intelligence); object detection; robot vision; support vector machines; AdaBoost; HOG; advanced robots; driver assistance systems; feature descriptor; histogram-of-oriented gradients; linear support vector machines; vision based pedestrian detection system; Cameras; Detectors; Histograms; Image sequences; Support vector machines; Vehicles; Videos; Adaboost; Histogram of Oriented Gradients; Linear Support Vector Machines; Pedestrian detection;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2012 - 2012 IEEE Region 10 Conference

Conference_Location

Cebu

ISSN

2159-3442

Print_ISBN

978-1-4673-4823-2

Electronic_ISBN

2159-3442

Type

conf

DOI

10.1109/TENCON.2012.6412236

Filename

6412236