Gesture Recognition Using Web Camera

Gesture recognition represents an important ability by which a computer is able to directly accept human gesture as input to trigger different actions just like conventional input devices such as keyboard. mouse, joystick and etc. As the Human Computer Interaction (HCI) progresses over the years,...

Full description

Saved in:
Bibliographic Details
Main Author: Lew, Yuan Fok
Format: Thesis
Language:English
Published: 2004
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/5907/1/FK_2004_25%20IR.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-upm-ir.5907
record_format uketd_dc
spelling my-upm-ir.59072022-02-03T02:22:22Z Gesture Recognition Using Web Camera 2004-02 Lew, Yuan Fok Gesture recognition represents an important ability by which a computer is able to directly accept human gesture as input to trigger different actions just like conventional input devices such as keyboard. mouse, joystick and etc. As the Human Computer Interaction (HCI) progresses over the years, emphasis is placed more on developing input devices which are most convenient and easy to use. Human gesture is not only natural and intuitive to a user, but can also represent motions of high degree of freedom which is of utmost importance in many applications especially in virtual reality. This thesis presents the design of an offline system which is capable of recognizing hand postures from the visual input of a web camera. The hand segmentation is based on image subtraction technique and a skin color modeling process. Fourier descriptors are used as the features to describe the geometry of different hand postures while the recognition process is based on minimum distance classifier. The results obtained indicate that the system is able to recognize hand postures with reasonable accuracy Human-computer interaction - Case studies Gesture 2004-02 Thesis http://psasir.upm.edu.my/id/eprint/5907/ http://psasir.upm.edu.my/id/eprint/5907/1/FK_2004_25%20IR.pdf text en public masters Universiti Putra Malaysia Human-computer interaction - Case studies Gesture Engineering Ramli, Abdul Rahman
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
advisor Ramli, Abdul Rahman
topic Human-computer interaction - Case studies
Gesture

spellingShingle Human-computer interaction - Case studies
Gesture

Lew, Yuan Fok
Gesture Recognition Using Web Camera
description Gesture recognition represents an important ability by which a computer is able to directly accept human gesture as input to trigger different actions just like conventional input devices such as keyboard. mouse, joystick and etc. As the Human Computer Interaction (HCI) progresses over the years, emphasis is placed more on developing input devices which are most convenient and easy to use. Human gesture is not only natural and intuitive to a user, but can also represent motions of high degree of freedom which is of utmost importance in many applications especially in virtual reality. This thesis presents the design of an offline system which is capable of recognizing hand postures from the visual input of a web camera. The hand segmentation is based on image subtraction technique and a skin color modeling process. Fourier descriptors are used as the features to describe the geometry of different hand postures while the recognition process is based on minimum distance classifier. The results obtained indicate that the system is able to recognize hand postures with reasonable accuracy
format Thesis
qualification_level Master's degree
author Lew, Yuan Fok
author_facet Lew, Yuan Fok
author_sort Lew, Yuan Fok
title Gesture Recognition Using Web Camera
title_short Gesture Recognition Using Web Camera
title_full Gesture Recognition Using Web Camera
title_fullStr Gesture Recognition Using Web Camera
title_full_unstemmed Gesture Recognition Using Web Camera
title_sort gesture recognition using web camera
granting_institution Universiti Putra Malaysia
granting_department Engineering
publishDate 2004
url http://psasir.upm.edu.my/id/eprint/5907/1/FK_2004_25%20IR.pdf
_version_ 1747810506957127680