Human pose estimation based on data-driven Monte Carlo hidden Markov models

Estimating human poses from 2D images or video sequences can provide the moving trajectories of the body joints for the high level processing, human activity recognition, which is applicable in surveillance, human-computer interaction and clinical and sport analysis. This project proposes a new stat...

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Bibliographic Details
Main Author:	Tao, Meng
Other Authors:	Yau Wei Yun
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Computer science and engineering::Computing methodologies DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Online Access:	https://hdl.handle.net/10356/3416
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Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-3416
record_format	dspace
spelling	sg-ntu-dr.10356-34162023-07-04T16:55:41Z Human pose estimation based on data-driven Monte Carlo hidden Markov models Tao, Meng Yau Wei Yun Chua Chin Seng School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Estimating human poses from 2D images or video sequences can provide the moving trajectories of the body joints for the high level processing, human activity recognition, which is applicable in surveillance, human-computer interaction and clinical and sport analysis. This project proposes a new statistical formulation called the data-driven Monte Carlo hidden Markov model to estimate human poses from random initializations. MASTER OF ENGINEERING (EEE) 2008-09-17T09:29:38Z 2008-09-17T09:29:38Z 2007 2007 Thesis Tao, M. (2007). Human pose estimation based on data-driven Monte Carlo hidden Markov models. Master’s thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3416 10.32657/10356/3416 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Computer science and engineering::Computing methodologies DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
spellingShingle	DRNTU::Engineering::Computer science and engineering::Computing methodologies DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Tao, Meng Human pose estimation based on data-driven Monte Carlo hidden Markov models
description	Estimating human poses from 2D images or video sequences can provide the moving trajectories of the body joints for the high level processing, human activity recognition, which is applicable in surveillance, human-computer interaction and clinical and sport analysis. This project proposes a new statistical formulation called the data-driven Monte Carlo hidden Markov model to estimate human poses from random initializations.
author2	Yau Wei Yun
author_facet	Yau Wei Yun Tao, Meng
format	Theses and Dissertations
author	Tao, Meng
author_sort	Tao, Meng
title	Human pose estimation based on data-driven Monte Carlo hidden Markov models
title_short	Human pose estimation based on data-driven Monte Carlo hidden Markov models
title_full	Human pose estimation based on data-driven Monte Carlo hidden Markov models
title_fullStr	Human pose estimation based on data-driven Monte Carlo hidden Markov models
title_full_unstemmed	Human pose estimation based on data-driven Monte Carlo hidden Markov models
title_sort	human pose estimation based on data-driven monte carlo hidden markov models
publishDate	2008
url	https://hdl.handle.net/10356/3416
_version_	1772826635640242176

Human pose estimation based on data-driven Monte Carlo hidden Markov models

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