Human posture and action recognition

Digital image processing is a very interesting subject. Although it is a relatively new field in technology, digital image processing has impacted the everyday lives of people all around the world. From Adobe® Photoshop© to the use of webcams, digital image processing has been used by people from al...

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Main Author: Lau, Melvin Eng Heok.
Other Authors: Maylor Karhang Leung
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/16942
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-169422023-03-03T20:54:17Z Human posture and action recognition Lau, Melvin Eng Heok. Maylor Karhang Leung School of Computer Engineering Forensics and Security Lab DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Digital image processing is a very interesting subject. Although it is a relatively new field in technology, digital image processing has impacted the everyday lives of people all around the world. From Adobe® Photoshop© to the use of webcams, digital image processing has been used by people from all walks of life, no matter if these people are professionals or not. However, there still exist many unexplored territories in digital image processing, especially with the techniques of pattern recognition. Therefore, it was the decision to base this project off MATLAB© 7.4, an engineering software which is commonly used for digital image processing applications. Learning to use MATLAB© was a very difficult task, but it was proven to be a good choice of software as it provided many powerful tools for image processing and had a very big and established online community to provide support. In this project, a couple of pattern recognition techniques was studied and slightly altered as a part of the exploration of a new pattern recognition technique, which was also used for human posture recognition. In this new technique, the author attempted to take an image pose and break it up into 4 different parts. Features, such as Zernike moments, were then extracted from these parts to be used for the recognition process. Tests were carried out in different test phases and in a modular manner. These test phases were mainly designed to ensure that the various components of the system worked individually, and also worked when integrated as a whole system. They were also designed to test the feasibility of this new technique, whether it was feasible or not to implement such a technique. Current results were satisfactory, but various problems, such as high processor utilisation, were identified when using this technique as well. The author feels that more improvements can be applied onto the project for better results. Bachelor of Engineering (Computer Engineering) 2009-05-29T02:17:13Z 2009-05-29T02:17:13Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/16942 en Nanyang Technological University 68 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Lau, Melvin Eng Heok.
Human posture and action recognition
description Digital image processing is a very interesting subject. Although it is a relatively new field in technology, digital image processing has impacted the everyday lives of people all around the world. From Adobe® Photoshop© to the use of webcams, digital image processing has been used by people from all walks of life, no matter if these people are professionals or not. However, there still exist many unexplored territories in digital image processing, especially with the techniques of pattern recognition. Therefore, it was the decision to base this project off MATLAB© 7.4, an engineering software which is commonly used for digital image processing applications. Learning to use MATLAB© was a very difficult task, but it was proven to be a good choice of software as it provided many powerful tools for image processing and had a very big and established online community to provide support. In this project, a couple of pattern recognition techniques was studied and slightly altered as a part of the exploration of a new pattern recognition technique, which was also used for human posture recognition. In this new technique, the author attempted to take an image pose and break it up into 4 different parts. Features, such as Zernike moments, were then extracted from these parts to be used for the recognition process. Tests were carried out in different test phases and in a modular manner. These test phases were mainly designed to ensure that the various components of the system worked individually, and also worked when integrated as a whole system. They were also designed to test the feasibility of this new technique, whether it was feasible or not to implement such a technique. Current results were satisfactory, but various problems, such as high processor utilisation, were identified when using this technique as well. The author feels that more improvements can be applied onto the project for better results.
author2 Maylor Karhang Leung
author_facet Maylor Karhang Leung
Lau, Melvin Eng Heok.
format Final Year Project
author Lau, Melvin Eng Heok.
author_sort Lau, Melvin Eng Heok.
title Human posture and action recognition
title_short Human posture and action recognition
title_full Human posture and action recognition
title_fullStr Human posture and action recognition
title_full_unstemmed Human posture and action recognition
title_sort human posture and action recognition
publishDate 2009
url http://hdl.handle.net/10356/16942
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