MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION

Markerless articulated human motion tracking is an emerging tield with potential applications in areas such as automatic smart security surveillance. medical rehabilitation. computer based animations in games and movie industries. The primary objective of markerless articulated human motion track...

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Main Author: SAINI, SANJA Y
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:http://utpedia.utp.edu.my/id/eprint/21559/1/2015%20-INFORMATION%20TECHNOLOGY%20-%20MARKERLESS%20ARTICULATED%20HUMAN%20MOTION%20TRACKING%20USING%20HIERARCHICAL%20MULTI-SWARM%20COOPERATIVE%20%20PARTICLE%20SWARM%20OPTIMIZATION%20-%20SANJAY%20SAINI.pdf
http://utpedia.utp.edu.my/id/eprint/21559/
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spelling oai:utpedia.utp.edu.my:215592024-07-25T04:35:22Z http://utpedia.utp.edu.my/id/eprint/21559/ MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION SAINI, SANJA Y QA75 Electronic computers. Computer science Markerless articulated human motion tracking is an emerging tield with potential applications in areas such as automatic smart security surveillance. medical rehabilitation. computer based animations in games and movie industries. The primary objective of markerless articulated human motion tracking is to automatically infer human pose. expressed in tenms of joint angles from a video stream (sequences of images). However. extracting the articulated human body motion from multi-view synchronized video stream is a dit1icult task due to the underlying multimodal and high dimensional estimation problem. The Particle Filtering (PF) algorithm is the most extensively used tor generative model based articulated human motion tracking. However. it suffers from ·curse of dimensionality' and the challenge of ·particle degeneracy'. Furthermore. PF algorithm requires manual initialization and needs a sequence-specific motion model. Most recently. the swarm-intelligence based PSO algorithm have been gaining momentum in this tield. 2016-06 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/21559/1/2015%20-INFORMATION%20TECHNOLOGY%20-%20MARKERLESS%20ARTICULATED%20HUMAN%20MOTION%20TRACKING%20USING%20HIERARCHICAL%20MULTI-SWARM%20COOPERATIVE%20%20PARTICLE%20SWARM%20OPTIMIZATION%20-%20SANJAY%20SAINI.pdf SAINI, SANJA Y (2016) MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION. Doctoral thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
SAINI, SANJA Y
MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
description Markerless articulated human motion tracking is an emerging tield with potential applications in areas such as automatic smart security surveillance. medical rehabilitation. computer based animations in games and movie industries. The primary objective of markerless articulated human motion tracking is to automatically infer human pose. expressed in tenms of joint angles from a video stream (sequences of images). However. extracting the articulated human body motion from multi-view synchronized video stream is a dit1icult task due to the underlying multimodal and high dimensional estimation problem. The Particle Filtering (PF) algorithm is the most extensively used tor generative model based articulated human motion tracking. However. it suffers from ·curse of dimensionality' and the challenge of ·particle degeneracy'. Furthermore. PF algorithm requires manual initialization and needs a sequence-specific motion model. Most recently. the swarm-intelligence based PSO algorithm have been gaining momentum in this tield.
format Thesis
author SAINI, SANJA Y
author_facet SAINI, SANJA Y
author_sort SAINI, SANJA Y
title MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
title_short MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
title_full MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
title_fullStr MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
title_full_unstemmed MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION
title_sort markerless articulated human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization
publishDate 2016
url http://utpedia.utp.edu.my/id/eprint/21559/1/2015%20-INFORMATION%20TECHNOLOGY%20-%20MARKERLESS%20ARTICULATED%20HUMAN%20MOTION%20TRACKING%20USING%20HIERARCHICAL%20MULTI-SWARM%20COOPERATIVE%20%20PARTICLE%20SWARM%20OPTIMIZATION%20-%20SANJAY%20SAINI.pdf
http://utpedia.utp.edu.my/id/eprint/21559/
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score 13.222552