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人机交互中的眼动跟踪Eye Gaze Tracking for Human Computer Interaction.pdf
1 Introduction
1.1 Motivation
1.2 Eye Gaze and Human Communication
1.3 Eye Gaze for Computer Input
1.4 Methods and Approach
1.5 Thesis Outline
1.6 Contributions
2 Overview and Related Work
2.1 Definition of Eye Tracking
2.2 History of Eye Tracking
2.3 Application Domains for Eye Tracking
2.4 Technological Basics of Eye Tracking
2.4.1 Methods of Eye Tracking
2.4.2 Video-Based Eye Tracking
2.4.3 The Corneal Reflection Method
2.5 Available Video-Based Eye Tracker Systems
2.5.1 Types of Video-Based Eye Trackers
2.5.2 Low-Cost Open Source Eye Trackers for HCI
2.5.3 Commercial Eye Trackers for HCI
2.5.4 Criteria for the Quality of an Eye Tracker
2.6 The ERICA Eye Tracker
2.6.1 Specifications
2.6.2 Geometry of the Experimental Setup
2.6.3 The ERICA-API
2.7 Related Work on Interaction by Gaze
2.8 Current Challenges
3 The Eye and its Movements
3.1 Anatomy and Movements of the Eye
3.2 Accuracy, Calibration and Anatomy
3.3 Statistics on Saccades and Fixations
3.3.1 The Data
3.3.2 Saccades Lengths
3.3.3 Saccade Speed
3.3.4 Fixation Times
3.3.5 Summary of Statistics
3.4 Speed and Accuracy
3.4.1 Eye Speed Models
3.4.2 Fitts’ Law
3.4.3 The Debate on Fitts’ Law for Eye Movements
3.4.4 The Screen Key Experiment
3.4.5 The Circle Experiment
3.4.6 Ballistic or Feedback-Controlled Saccades
3.4.7 Conclusions on Fitts’ Law for the Eyes
4 Eye Gaze as Pointing Device
4.1 Overview on Pointing Devices
4.1.1 Properties of Pointing Devices
4.1.2 Problems with Traditional Pointing Devices
4.1.3 Problems with Eye Gaze as Pointing Device
4.2 Related Work for Eye Gaze as Pointing Device
4.3 MAGIC Pointing with a Touch-Sensitive Mouse Device
4.4 User Studies with the Touch-Sensitive Mouse Device
4.4.1 First User Study – Testing the Concept
4.4.2 Second User Study – Learning and Hand-Eye Coordination
4.4.3 Third User Study – Raw and Fine Positioning
4.5 A Deeper Understanding of MAGIC Touch
4.6 Summary on the Results for Eye Gaze as Pointing Device
4.7 Conclusions on Eye Gaze as Pointing Device
5 Gaze Gestures
5.1 Related Work on Gaze Gestures
5.2 The Concept of Gaze Gestures
5.2.1 The Firefox/Opera Mouse Gestures
5.2.2 The EdgeWrite Gestures
5.3 The Gaze Gesture Recognition Algorithm
5.4 User Studies and Experiments with Gaze Gestures
5.4.1 First User Study – Testing the Concept
5.4.2 Experiments – When to Use Gaze Gestures
5.4.3 Second User Study – Optimizing the Parameters
5.4.4 Mobile Phone User Study
5.4.5 PIN-Entry User Study
5.5 The Gaze Gesture Alphabet
5.6 Separation of Gaze Gestures from Natural Eye Movements
5.7 Summary of the Results for Gaze Gestures
5.8 Conclusions for Gaze Gestures
6 Eye Gaze as Context Information
6.1 Eye Gaze and Context Awareness
6.2 Related Work for Eye Gaze as Context Information
6.3 A Usability Tool to Record Eye Movements
6.3.1 Explanation of UsaProxy
6.3.2 Extending UsaProxy to Record Eye Movements
6.3.3 Discussion of UsaProxy’s Extension
6.4 Reading Detection
6.4.1 Analysis of the Gaze Path while Reading
6.4.2 An Algorithm for Reading Detection
6.4.3 User Study for Reading Detection
6.4.4 Values for the Quality of Reading
6.5 Gaze-Awareness in E-Learning Environments
6.6 Summary of the Results for Eye Gaze as Context Information
6.7 Conclusions on Eye Gaze as Context Information
7 Conclusions
7.1 Summary of the Results
7.2 Conclusions for Eye Gaze User Interfaces
7.3 How to go on with Eye-Tracking Research for Interaction
7.4 The Future of Gaze-Aware Systems
References
Web References
Acknowledgements
Eye Gaze Tracking for
Human Computer Interaction
Heiko Drewes
Dissertation
an der LFE Medien-Informatik
der Ludwig-Maximilians-Universität
München
München 2010
Erstgutachter:
Zweitgutachter:
Externer Gutachter:
Tag der mündlichen Prüfung:
Professor Dr. Heinrich Hußmann
Professor Dr. Albrecht Schmidt
Professor Dr. Alan Dix
18.3.2010
Abstract
With a growing number of computer devices around us, and the increasing time we spend for interacting with
such devices, we are strongly interested in finding new interaction methods which ease the use of computers or
increase interaction efficiency. Eye tracking seems to be a promising technology to achieve this goal.
This thesis researches interaction methods based on eye-tracking technology. After a discussion of the limitations
of the eyes regarding accuracy and speed, including a general discussion on Fitts’ law, the thesis follows three
different approaches on how to utilize eye tracking for computer input. The first approach researches eye gaze as
pointing device in combination with a touch sensor for multimodal input and presents a method using a touch
sensitive mouse. The second approach examines people’s ability to perform gestures with the eyes for computer
input and the separation of gaze gestures from natural eye movements. The third approach deals with the
information inherent in the movement of the eyes and its application to assist the user. The thesis presents a
usability tool for recording of interaction and gaze activity. It also describes algorithms for reading detection.
All approaches present results based on user studies conducted with prototypes developed for the purpose.
Zusammenfassung
Mit einer wachsenden Zahl von Computergeräten um uns herum und zunehmender Zeit die wir mit der
Bedienung dieser Geräte zubringen, haben wir ein großes Interesse daran, Interaktionsmethoden zu finden,
welche die Benutzung der Computer erleichtern oder effizienter machen. Blickverfolgung scheint eine viel
versprechende Technologie zu sein um dieses Ziel zu erreichen.
Die vorliegende Arbeit untersucht Interaktionsmethoden, die auf Blickverfolgertechnik beruhen. Nach einer
Diskussion der Beschränkungen des Auges in Bezug auf Genauigkeit und Geschwindigkeit, die eine generelle
Diskussion des Fitts’ Law enthält, verfolgt die Arbeit drei verschiedene Ansätze wie Blickverfolgung für
Computereingaben benutzt werden kann. Der erste Ansatz untersucht den Blick als Zeigegerät in Kombination
mit einem Berührungssensor für multimodale Eingabe und stellt eine Methode mit einer berührungsempfind-
lichen Maus vor. Der zweite Ansatz untersucht die Fähigkeit von Menschen Gesten mit den Augen für
Computereingaben durchzuführen und wie diese Blickgesten von natürlichen Augenbewegungen unterschieden
werden können. Der dritte Ansatz beschäftigt sich mit der Information, die den Augenbewegungen entnommen
werden kann, und ihrer Anwendung zur Unterstützung der Benutzer. Es wird ein Usability-Werkzeug zum Auf-
zeichnen von Interaktions- und Blickaktivität vorgestellt. Außerdem werden Algorithmen zur Leseerkennung
beschrieben.
Für alle Ansätze werden Ergebnisse präsentiert, die auf durchgeführten Benutzerstudien mit speziell entwickel-
ten Prototypen beruhen.
Introduction
Motivation
Eye Gaze and Human Communication
Eye Gaze for Computer Input
Methods and Approach
Thesis Outline
Contributions
Overview and Related Work
Definition of Eye Tracking
History of Eye Tracking
Application Domains for Eye Tracking
Technological Basics of Eye Tracking
Methods of Eye Tracking
Video-Based Eye Tracking
The Corneal Reflection Method
Available Video-Based Eye Tracker Systems
Types of Video-Based Eye Trackers
Low-Cost Open Source Eye Trackers for HCI
Commercial Eye Trackers for HCI
Criteria for the Quality of an Eye Tracker
The ERICA Eye Tracker
Specifications
Geometry of the Experimental Setup
The ERICA-API
Related Work on Interaction by Gaze
Current Challenges
The Eye and its Movements
Anatomy and Movements of the Eye
Accuracy, Calibration and Anatomy
Table of Contents
6
6
7
9
11
11
12
14
14
15
16
18
18
19
20
21
21
22
23
25
26
26
27
27
29
31
33
33
35
2
1
1.1
1.2
1.3
1.4
1.5
1.6
2
2.1
2.2
2.3
2.4
2.4.1
2.4.2
2.4.3
2.5
2.5.1
2.5.2
2.5.3
2.5.4
2.6
2.6.1
2.6.2
2.6.3
2.7
2.8
3
3.1
3.2
Statistics on Saccades and Fixations
The Data
Saccades Lengths
Saccade Speed
Fixation Times
Summary of Statistics
Speed and Accuracy
Eye Speed Models
Fitts’ Law
The Debate on Fitts’ Law for Eye Movements
The Screen Key Experiment
The Circle Experiment
Ballistic or Feedback-Controlled Saccades
Conclusions on Fitts’ Law for the Eyes
Eye Gaze as Pointing Device
Overview on Pointing Devices
Properties of Pointing Devices
Problems with Traditional Pointing Devices
Problems with Eye Gaze as Pointing Device
Related Work for Eye Gaze as Pointing Device
MAGIC Pointing with a Touch-Sensitive Mouse Device
User Studies with the Touch-Sensitive Mouse Device
First User Study – Testing the Concept
Second User Study – Learning and Hand-Eye Coordination
Third User Study – Raw and Fine Positioning
A Deeper Understanding of MAGIC Touch
Summary on the Results for Eye Gaze as Pointing Device
Conclusions on Eye Gaze as Pointing Device
Gaze Gestures
Related Work on Gaze Gestures
3
38
39
39
42
43
45
47
47
48
56
63
65
69
72
74
74
74
75
76
77
79
81
81
87
94
95
97
97
99
99
Table of Contents
3.3
3.3.1
3.3.2
3.3.3
3.3.4
3.3.5
3.4
3.4.1
3.4.2
3.4.3
3.4.4
3.4.5
3.4.6
3.4.7
4
4.1
4.1.1
4.1.2
4.1.3
4.2
4.3
4.4
4.4.1
4.4.2
4.4.3
4.5
4.6
4.7
5
5.1
4
5.2
5.2.1
5.2.2
5.3
5.4
5.4.1
5.4.2
5.4.3
5.4.4
5.4.5
5.5
5.6
5.7
5.8
6
6.1
6.2
6.3
6.3.1
6.3.2
6.3.3
6.4
6.4.1
6.4.2
6.4.3
6.4.4
6.5
6.6
6.7
7
Table of Contents
The Concept of Gaze Gestures
The Firefox/Opera Mouse Gestures
The EdgeWrite Gestures
The Gaze Gesture Recognition Algorithm
User Studies and Experiments with Gaze Gestures
First User Study – Testing the Concept
Experiments – When to Use Gaze Gestures
Second User Study – Optimizing the Parameters
Mobile Phone User Study
PIN-Entry User Study
The Gaze Gesture Alphabet
Separation of Gaze Gestures from Natural Eye Movements
Summary of the Results for Gaze Gestures
Conclusions for Gaze Gestures
Eye Gaze as Context Information
Eye Gaze and Context Awareness
Related Work for Eye Gaze as Context Information
A Usability Tool to Record Eye Movements
Explanation of UsaProxy
Extending UsaProxy to Record Eye Movements
Discussion of UsaProxy’s Extension
Reading Detection
Analysis of the Gaze Path while Reading
An Algorithm for Reading Detection
User Study for Reading Detection
Values for the Quality of Reading
Gaze-Awareness in E-Learning Environments
100
100
101
101
103
103
107
109
111
114
117
119
122
123
124
124
125
127
127
128
130
132
132
133
135
136
138
Summary of the Results for Eye Gaze as Context Information 138
Conclusions on Eye Gaze as Context Information
Conclusions
139
140
Summary of the Results
Conclusions for Eye Gaze User Interfaces
How to go on with Eye-Tracking Research for Interaction
The Future of Gaze-Aware Systems
Table of Contents
7.1
7.2
7.3
7.4
References
Web References
Acknowledgements
5
140
141
145
146
149
162
164
Introduction
1
6
Eye Gaze Tracking for Human Computer
Interaction
1
Introduction
With the invention of the computer in the middle of the last century there was also the need of an interface for
users. In the beginning experts used teletype to interface with the computer. Due to the tremendous progress in
computer technology in the last decades, the capabilities of computers increased enormously and working with a
computer became a normal activity for nearly everybody. With all the possibilities a computer can offer, humans
and their interaction with computers are now a limiting factor. This gave rise to a lot of research in the field of
HCI (human computer interaction) aiming to make interaction easier, more intuitive, and more efficient.
Interaction with computers is not limited to keyboards and printers anymore. Different kinds of pointing devices,
touch-sensitive surfaces, high-resolution displays, microphones, and speakers are normal devices for computer
interaction nowadays. There are new modalities for computer interaction like speech interaction, input by
gestures or by tangible objects with sensors. A further input modality is eye gaze which nowadays finds its
application in accessibility systems. Such systems typically use eye gaze as the sole input, but outside the field of
accessibility eye gaze can be combined with any other input modality. Therefore, eye gaze could serve as an
interaction method beyond the field of accessibility. The aim of this work is to find new forms of interactions
utilizing eye gaze and suitable for standard users.
1.1 Motivation
Nowadays most eye-tracking systems work on video-based pupil detection and a reflection of an infrared LED.
Video cameras became cheap over the last years and the price for a LED is negligible. Many computer devices
come already with built-in cameras, such as mobile phones, laptops, and displays. Processor power still increases
steadily and standard processors are powerful enough to process the video stream necessary to do eye tracking,
at least on desktop and laptop computers. Head-tracking systems, which are necessary to give the users the
freedom to move in front of their display, are also video-based. Such systems can be implemented unobtrusively
with a second camera. If produced for the mass market, a future standard eye tracker should not cost much more
than an optical mouse or a webcam today.
Some people interact with the computer all day long, for their work and in their leisure time. As most interaction
is done with keyboard and mouse, both using the hands, some people suffer from overstressing particular parts of
their hands, typically causing a carpal tunnel syndrome. With a vision of ubiquitous computing, the amount of
interaction with computers will increase and we are in need of interaction techniques which do not cause
physical problems. The eyes are a good candidate because they move anyway when interacting with computers.
Using the information lying in the eye movements could save some interaction, in particular hand-based
interaction.
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