test Browse by Author Names Browse by Titles of Works Browse by Subjects of Works Browse by Issue Dates of Works

Advanced Search
& Collections
Issue Date   
Sign on to:   
Receive email
My Account
authorized users
Edit Profile   
About T-Space   

T-Space at The University of Toronto Libraries >
School of Graduate Studies - Theses >
Master >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/30546

Title: Facial Feature Point Detection
Authors: Chen, Fang
Advisor: Plataniotis, Konstantinos N.
Department: Electrical and Computer Engineering
Keywords: computer vision
image processing
Issue Date: 6-Dec-2011
Abstract: Facial feature point detection is a key issue in facial image processing. One main challenge of facial feature point detection is the variation of facial structures due to expressions. This thesis aims to explore more accurate and robust facial feature point detection algorithms, which can facilitate the research on facial image processing, in particular the facial expression analysis. This thesis introduces a facial feature point detection system, where the Multilinear Principal Component Analysis is applied to extract the highly descriptive features of facial feature points. In addition, to improve the accuracy and efficiency of the system, a skin color based face detection algorithm is studied. The experiment results have indicated that this system is effective in detecting 20 facial feature points in frontal faces with different expressions. This system has also achieved a higher accuracy during the comparison with the state-of-the-art, BoRMaN.
URI: http://hdl.handle.net/1807/30546
Appears in Collections:Master

Files in This Item:

File Description SizeFormat
Chen_Fang_201111_MASc_Thesis.pdf4.71 MBAdobe PDF

This item is licensed under a Creative Commons License
Creative Commons

Items in T-Space are protected by copyright, with all rights reserved, unless otherwise indicated.