Face detection using skin color and eigenface techniques for human-robot interaction

The main objective of the research undertaken here is to develop an automated face detection system to be implemented on a mobile robot for humanrobot interaction (HRI) applications. HRI has gained increasing attention in recent years due to escalating numbers of assimilation of robots into human li...

Full description

Saved in:

Bibliographic Details
Main Author:	Wong, Hwee Ling
Format:	Thesis
Language:	English
Published:	2005
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/4327/1/WongHweeLingMFKE2005.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.4327
record_format	uketd_dc
spelling	my-utm-ep.43272018-01-22T04:05:17Z Face detection using skin color and eigenface techniques for human-robot interaction 2005-05 Wong, Hwee Ling TK Electrical engineering. Electronics Nuclear engineering The main objective of the research undertaken here is to develop an automated face detection system to be implemented on a mobile robot for humanrobot interaction (HRI) applications. HRI has gained increasing attention in recent years due to escalating numbers of assimilation of robots into human lives. Face detection is a vital aspect to sense human presence in a robotic environment. Despite the fact that research on face detection has long been carried out, development and implementation of face detection on mobile robot remains a great challenge due to the complexity of the robot itself. A HRI model is presented to represent a humanrobot relationship in the shared robotic environment. The work focuses in building a natural form one human to one robot HRI based on face detection. The main concern of the work is to develop face detection using multiple features to increase robustness of the system. The face detection comprises of a skin color detection based on various chrominance information of images using multiple color spaces. Later, the skin region is verified using crisp rules face verification. Different rules are applied at different robot behavior that accommodates the HRI. Where applicable, eigenface method is implemented for further verification. Later, the robot makes decision and reacts based on the face detection result using heuristic search on the decision tree. An adaptive weighting technique for the branches in the decision tree is presented to solve problem for various robot behaviors and noise in images. Graphical user interface (GUI) and text-to-voice ability are employed on the robot to support HRI. Through experiments, it appears that the robot can successfully detect human face and react meaningfully towards the face that has been detected. 2005-05 Thesis http://eprints.utm.my/id/eprint/4327/ http://eprints.utm.my/id/eprint/4327/1/WongHweeLingMFKE2005.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Wong, Hwee Ling Face detection using skin color and eigenface techniques for human-robot interaction
description	The main objective of the research undertaken here is to develop an automated face detection system to be implemented on a mobile robot for humanrobot interaction (HRI) applications. HRI has gained increasing attention in recent years due to escalating numbers of assimilation of robots into human lives. Face detection is a vital aspect to sense human presence in a robotic environment. Despite the fact that research on face detection has long been carried out, development and implementation of face detection on mobile robot remains a great challenge due to the complexity of the robot itself. A HRI model is presented to represent a humanrobot relationship in the shared robotic environment. The work focuses in building a natural form one human to one robot HRI based on face detection. The main concern of the work is to develop face detection using multiple features to increase robustness of the system. The face detection comprises of a skin color detection based on various chrominance information of images using multiple color spaces. Later, the skin region is verified using crisp rules face verification. Different rules are applied at different robot behavior that accommodates the HRI. Where applicable, eigenface method is implemented for further verification. Later, the robot makes decision and reacts based on the face detection result using heuristic search on the decision tree. An adaptive weighting technique for the branches in the decision tree is presented to solve problem for various robot behaviors and noise in images. Graphical user interface (GUI) and text-to-voice ability are employed on the robot to support HRI. Through experiments, it appears that the robot can successfully detect human face and react meaningfully towards the face that has been detected.
format	Thesis
qualification_level	Master's degree
author	Wong, Hwee Ling
author_facet	Wong, Hwee Ling
author_sort	Wong, Hwee Ling
title	Face detection using skin color and eigenface techniques for human-robot interaction
title_short	Face detection using skin color and eigenface techniques for human-robot interaction
title_full	Face detection using skin color and eigenface techniques for human-robot interaction
title_fullStr	Face detection using skin color and eigenface techniques for human-robot interaction
title_full_unstemmed	Face detection using skin color and eigenface techniques for human-robot interaction
title_sort	face detection using skin color and eigenface techniques for human-robot interaction
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2005
url	http://eprints.utm.my/id/eprint/4327/1/WongHweeLingMFKE2005.pdf
_version_	1747814516014448640

Face detection using skin color and eigenface techniques for human-robot interaction

Similar Items