Date of Publication
4-2012
Document Type
Master's Thesis
Degree Name
Master of Science in Mechanical Engineering
Subject Categories
Mechanical Engineering
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Thesis Adviser
Alvin Y. Chua
Defense Panel Chair
Laurence A. Gan Lim
Defense Panel Member
Edwin Sybingco
Isidro V. Marfori
Abstract/Summary
Pedestrian detection systems are valuable in a variety of applications including advanced driver assistance systems and advanced robots. This study aims to develop a vision-based pedestrian detection system for moving platforms. It uses Histogram of Oriented Gradients (HOG) as feature descriptor, AdaBoost and Linear Support Vector Machines (SVM) as a classifiers and Optical Flow for discerning the pedestrians direction. 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 than default detector.
Abstract Format
html
Language
English
Format
Electronic
Electronic File Format
MS WORD
Accession Number
CDTG005130
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
88 leaves : ill. ; 1 computer optical disc
Keywords
Pedestrians
Upload Full Text
wf_yes
Recommended Citation
Hilado, S. (2012). Vision based pedestrian detection using histogram of oriented gradients, adaboost, linear support vector machines and optical flow. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/4128
