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Reseach Article

Pedestrian Detection and Tracking based on Particle Filtering using HOG Features and Neural Network

by Urooj Fatima, Jaykant Pratap Singh Yadav, Raj Kumar Goel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 173 - Number 4
Year of Publication: 2017
Authors: Urooj Fatima, Jaykant Pratap Singh Yadav, Raj Kumar Goel
10.5120/ijca2017915289

Urooj Fatima, Jaykant Pratap Singh Yadav, Raj Kumar Goel . Pedestrian Detection and Tracking based on Particle Filtering using HOG Features and Neural Network. International Journal of Computer Applications. 173, 4 ( Sep 2017), 30-32. DOI=10.5120/ijca2017915289

@article{ 10.5120/ijca2017915289,
author = { Urooj Fatima, Jaykant Pratap Singh Yadav, Raj Kumar Goel },
title = { Pedestrian Detection and Tracking based on Particle Filtering using HOG Features and Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2017 },
volume = { 173 },
number = { 4 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = { 30-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume173/number4/28325-2017915289/ },
doi = { 10.5120/ijca2017915289 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:20:22.582328+05:30
%A Urooj Fatima
%A Jaykant Pratap Singh Yadav
%A Raj Kumar Goel
%T Pedestrian Detection and Tracking based on Particle Filtering using HOG Features and Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 173
%N 4
%P 30-32
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a neural network based approach for the detection and tracking of pedestrian. It addresses the problem of human detection and tracking in surveillance videos. This system consist of three major modules: Initially the video objects are detected using a novel temporal differencing based procedure and several mathematical morphology-based operations. On the basis of results, it was figured out that the Histogram of Oriented Gradient (HOG) and Relative Discriminative Histogram of Oriented Gradient (RDHOG) feature which were trained in the Neural Network classifiers have given a good performance within the expected process timing. Pedestrian tracking is the last part of the system. In this research we propose the tracking function which is based on the Particle filtering and a trustworthy pointing system. The movement and alteration in the size of the vehicles which are detected in continuous video frames are tracked by the function.

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Index Terms

Computer Science
Information Sciences

Keywords

HOG Pedestrian Detection Neural Network RDHOG