Human tracking for computer virtual reality applications

Computer vision is an interdisciplinary field related to many fields involving AI (Artificial Intelligence), robotics, geometry, computer programming, machine learning, signal processing etc. It is aggregations of ideologies from various fields with the purpose of creating a computer program or func...

Full description

Saved in:
Bibliographic Details
Main Author: Teo, Han Seng.
Other Authors: Shen Zhiqi
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/35240
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-35240
record_format dspace
spelling sg-ntu-dr.10356-352402023-07-07T16:12:42Z Human tracking for computer virtual reality applications Teo, Han Seng. Shen Zhiqi School of Electrical and Electronic Engineering A*STAR DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Computer vision is an interdisciplinary field related to many fields involving AI (Artificial Intelligence), robotics, geometry, computer programming, machine learning, signal processing etc. It is aggregations of ideologies from various fields with the purpose of creating a computer program or function to understand features in an image. In this Final Year Project, many techniques were explored for the purpose of developing the programming functions in a computer programming language Visual C++ to satisfy the milestones which were specified in “introduction” section. The report presents a unique process of training of the detector for hand postures detection and face detection while wearing glasses. Following such training the classifiers were tested in C++ programming environment. It was found that the classifier or detector could be improved by following a new process of training which was implemented in C++. Retesting with our new method showed remarkable improvements over previous results. Next part of the research under this projects us about development of a reliable method for skin detection. Extensive survey of existing techniques was conducted and a relatively known method for skin detection was successfully implemented. It was used to improve the performances of the face detector. The report concludes by presenting an application that controls the motion of the mouse in Windows XP environment using hand motion, and shows the effectiveness of the implemented techniques. The detector mentioned above was used for developing the application for controlling the mouse pointer was tuned to improve the accuracy of detection. It went through many rounds of the unique improvement process thought up for this project to improve the detection rate of the classifier in order to achieve good accuracy for controlling the mouse pointer in Windows XP environment. Bachelor of Engineering 2010-04-12T04:38:50Z 2010-04-12T04:38:50Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/35240 en Nanyang Technological University 81 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
Teo, Han Seng.
Human tracking for computer virtual reality applications
description Computer vision is an interdisciplinary field related to many fields involving AI (Artificial Intelligence), robotics, geometry, computer programming, machine learning, signal processing etc. It is aggregations of ideologies from various fields with the purpose of creating a computer program or function to understand features in an image. In this Final Year Project, many techniques were explored for the purpose of developing the programming functions in a computer programming language Visual C++ to satisfy the milestones which were specified in “introduction” section. The report presents a unique process of training of the detector for hand postures detection and face detection while wearing glasses. Following such training the classifiers were tested in C++ programming environment. It was found that the classifier or detector could be improved by following a new process of training which was implemented in C++. Retesting with our new method showed remarkable improvements over previous results. Next part of the research under this projects us about development of a reliable method for skin detection. Extensive survey of existing techniques was conducted and a relatively known method for skin detection was successfully implemented. It was used to improve the performances of the face detector. The report concludes by presenting an application that controls the motion of the mouse in Windows XP environment using hand motion, and shows the effectiveness of the implemented techniques. The detector mentioned above was used for developing the application for controlling the mouse pointer was tuned to improve the accuracy of detection. It went through many rounds of the unique improvement process thought up for this project to improve the detection rate of the classifier in order to achieve good accuracy for controlling the mouse pointer in Windows XP environment.
author2 Shen Zhiqi
author_facet Shen Zhiqi
Teo, Han Seng.
format Final Year Project
author Teo, Han Seng.
author_sort Teo, Han Seng.
title Human tracking for computer virtual reality applications
title_short Human tracking for computer virtual reality applications
title_full Human tracking for computer virtual reality applications
title_fullStr Human tracking for computer virtual reality applications
title_full_unstemmed Human tracking for computer virtual reality applications
title_sort human tracking for computer virtual reality applications
publishDate 2010
url http://hdl.handle.net/10356/35240
_version_ 1772826727259570176