Human activity recognition

The major goal of computer vision research is to be able to interpret human motion and activities. It is a challenging task to be able to implement an accurate human activity recognition system as human activity is complex and diverse. To date, large body of literatures focuses in the field of hu...

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Main Author: Chua, Wilson Wei Jie.
Other Authors: Jiang Xudong
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/52993
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-529932023-07-07T17:35:06Z Human activity recognition Chua, Wilson Wei Jie. Jiang Xudong School of Electrical and Electronic Engineering DRNTU::Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision The major goal of computer vision research is to be able to interpret human motion and activities. It is a challenging task to be able to implement an accurate human activity recognition system as human activity is complex and diverse. To date, large body of literatures focuses in the field of human activity recognition. While it is easy for a human to interpret some basic action/movement, such as walking or jumping when demonstrated by their peers, it is not possible for computer to distinguish the actions by itself, not without program that gives the computer the ability to do so. Since 1980s, human activity recognition has been gaining tremendous attention in the computer and machine vision world as many researchers are dedicated in this field through these decades. In this project, the aim is to implement an existing method to allow computer to learn the human activity and be able to recognize the human activity by the recognition process. Two methods of recognition process are proposed to determine which methods will give a better recognition rates. This system is written in C++, and an API, OpenCV is used to work on the system. The system will make use of Principle Components Analysis (PCA) to train human activity recognition. Bachelor of Engineering 2013-05-29T06:54:29Z 2013-05-29T06:54:29Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52993 en Nanyang Technological University 46 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
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Chua, Wilson Wei Jie.
Human activity recognition
description The major goal of computer vision research is to be able to interpret human motion and activities. It is a challenging task to be able to implement an accurate human activity recognition system as human activity is complex and diverse. To date, large body of literatures focuses in the field of human activity recognition. While it is easy for a human to interpret some basic action/movement, such as walking or jumping when demonstrated by their peers, it is not possible for computer to distinguish the actions by itself, not without program that gives the computer the ability to do so. Since 1980s, human activity recognition has been gaining tremendous attention in the computer and machine vision world as many researchers are dedicated in this field through these decades. In this project, the aim is to implement an existing method to allow computer to learn the human activity and be able to recognize the human activity by the recognition process. Two methods of recognition process are proposed to determine which methods will give a better recognition rates. This system is written in C++, and an API, OpenCV is used to work on the system. The system will make use of Principle Components Analysis (PCA) to train human activity recognition.
author2 Jiang Xudong
author_facet Jiang Xudong
Chua, Wilson Wei Jie.
format Final Year Project
author Chua, Wilson Wei Jie.
author_sort Chua, Wilson Wei Jie.
title Human activity recognition
title_short Human activity recognition
title_full Human activity recognition
title_fullStr Human activity recognition
title_full_unstemmed Human activity recognition
title_sort human activity recognition
publishDate 2013
url http://hdl.handle.net/10356/52993
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