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Detecting and Tracking of Multiple People in Video based on Hybrid Detection and Human Anatomy Body Proportion

by Amr El Maghraby, Mahmoud Abdalla, Othman Enany, Mohamed Y. El Nahas
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 17
Year of Publication: 2015
Authors: Amr El Maghraby, Mahmoud Abdalla, Othman Enany, Mohamed Y. El Nahas
10.5120/19416-0656

Amr El Maghraby, Mahmoud Abdalla, Othman Enany, Mohamed Y. El Nahas . Detecting and Tracking of Multiple People in Video based on Hybrid Detection and Human Anatomy Body Proportion. International Journal of Computer Applications. 109, 17 ( January 2015), 10-14. DOI=10.5120/19416-0656

@article{ 10.5120/19416-0656,
author = { Amr El Maghraby, Mahmoud Abdalla, Othman Enany, Mohamed Y. El Nahas },
title = { Detecting and Tracking of Multiple People in Video based on Hybrid Detection and Human Anatomy Body Proportion },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 17 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number17/19416-0656/ },
doi = { 10.5120/19416-0656 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:02.730241+05:30
%A Amr El Maghraby
%A Mahmoud Abdalla
%A Othman Enany
%A Mohamed Y. El Nahas
%T Detecting and Tracking of Multiple People in Video based on Hybrid Detection and Human Anatomy Body Proportion
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 17
%P 10-14
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper addresses problems of detection and tracking of moving multiple people in a video stream. Detecting and tracking are fundamental tasks for future research into Human Computer Interaction (HCI). Detecting and Tracking multiple people in video are considered time consuming processes due to the amount of data a video contains, illumination changes, complex backgrounds and occlusions that occur as soon as people change orientations over time. This study focus on developing a fully automated system aims to Detecting and tracking multiple people in video, by analyzes sequential video frames based on hybrid detection algorithm, and tracking based on human body structure. The performance of the proposed system is tested through a series of experiments and human computer interaction application based human detection, tracking and identification. Identification is based on new clustering method mentioned in this paper.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Video Processing Human detection and tracking Viola- Jones upper body Skin detection Computer vision systems Biometrics