Vision based pedestrian detection using histogram of oriented gradients, adaboost, linear support vector machines and optical flow

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ID: 286994
2012
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Abstract
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.
Reference Key
persistent_1760660277_68f18b358a65f Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hilado, Samantha Denise Fuentes
Journal Malay Journal
Year 2012
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etd_masteral/4128
Keywords Keywords not found

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