Page 1 |
Save page Remove page | Previous | 1 of 127 | Next |
|
small (250x250 max)
medium (500x500 max)
Large (1000x1000 max)
Extra Large
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
Facial Gesture Analysis In An Interactive Environment
by
Wei-Kai Liao
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful¯llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
August 2008
Copyright 2008 Wei-Kai Liao
Object Description
| Title | Facial gesture analysis in an interactive environment |
| Author | Liao, Wei-Kai |
| Author email | wliao@usc.edu; kai.liao@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-05-19 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-08-06 |
| Advisor (committee chair) | Medioni, Gerard |
| Advisor (committee member) |
Nevatia, Ramakant Kuo, C.-C. Jay |
| Abstract | This research focuses on tracking, modeling, quantifying and analyzing facial motions for gesture understanding. Facial gesture analysis is an important problem in computer vision since facial gestures carry signals besides words and are critical for nonverbal communication. The difficulty of automatic facial gesture recognition lies in the complexity of face motions. These motions can be categorized into two classes: global, rigid head motion, and local, nonrigid facial deformations. In reality, observed facial motions are a mixture of these two components.; In this work, we propose a framework to take both of these two motions into account. The whole framework consists of three components: 3D head pose estimation, modeling local deformations, and expression classification.; We propose a novel hybrid 3D head tracking algorithm to differentiate these two motions. The hybrid tracker integrates both intensity and feature correspondence information for robust real-time head pose estimation. Based on this tracker, we classify video segments into expressions by learning a graphical representation for nonrigid facial motions. The graphical model characterizes each face region by dense motion fields, and encodes inter-region dependencies in joint density functions. This graphical model is learned empirically using the EM algorithm and expression recognition is performed by Bayesian MAP estimation.; In addition, rigid and nonrigid motions are analyzed simultaneously in 3D by manifold learning techniques. We decompose nonrigid facial deformations on a basis of 1D manifolds. Each 1D manifold is learned offline from sequences of labeled basic expressions, such as smile, surprise, etc. Any expression is then a linear combination of values along these axes, with coefficient representing the level of activation. We experimentally verify that expressions can indeed be represented this way, and that individual manifolds are indeed 1D. The manifold learning and dimensionality estimation are all implemented in the N-D Tensor Voting framework. The output of our system is a rich representation of the face, including the 3D pose, 3D shape, expression label with probability, and the activation level. |
| Keyword | face; facial gestures; expression recognition; head pose estimation; 3D face tracking; tensor voting; manifold learning; graphical model; face alignment |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1551 |
| Contributing entity | University of Southern California |
| Rights | Liao, Wei-Kai |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@dots.usc.edu |
| Filename | etd-Liao-2237 |
| Archival file | uscthesesreloadpub_Volume26/etd-Liao-2237.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@dots.usc.edu |
| Full text | Facial Gesture Analysis In An Interactive Environment by Wei-Kai Liao A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful¯llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) August 2008 Copyright 2008 Wei-Kai Liao |
