blueeyes report

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A

SEMINAR

ONBLUE EYES TECHNOLOGY

By:-

Rohan Chugh

1531323107

Department of Information Technology

Guru Tegh Bahadur Institute of Technology

Guru Gobind Singh Indraprastha University

Kashmere Gate,New Delhi

Year 2010-2011

1



ACKNOWLEDGEMENT

I would like to express my great gratitude towards, Mr. Munshi Yadav

(H.O.D CSE/ IT Department) and Mr. Amanpreet Singh who has given

me support and suggestions. Without their help I could not have

presented this dissertation up to the present standard. I also take this

opportunity to thank everyone who helped me directly or indirectly in the

completion of this seminar.

Rohan Chugh

1531323107

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ABSTRACT

A study has shown that people with personalities that are similar collaborate well. Dryer (1999) has also shown that people view their

computer as having a personality. For these reasons, it is important to

develop computers which can work well with its user. This is where the

blue eyes technology comes into force. With the abilities to gather

information about you and interact with you through special techniques

like facial recognition, speech recognition, etc., it can even understand

your emotions at the touch of the mouse. It verifies your identity, feels

your presence, and starts interacting with you. So the ultimate aim of

BLUEEYES TECHNOLOGY is to create a user friendly system that canincrease the productivity of the user by adapting itself to the user’s mood.

With the eye tracker technology it can reduce the user’s work load. It will

move the cursor directly to the place where the user is staring at. The

additional facility of speech recognition bestows you with the ability to

just dictate commands to the computer while you can engage yourself

with some other work. Using eye tracker technology the computer can

use the SUITOR facility to provide the user additional info about the

topic he is reading/ looking at in a tab. This will for sure reduce his job of

having to search for the information all by himself. So this concept of BLUEEYE TECHNOLOGY IS SURELY A BOON. After all who

would not want to own a computer that:

(1) Can easily adapt to your mood,

(2) Perform tasks the moment you “actually tell” it what you want

(3) Help you by gathering more additional information

(4) Saves you the job of having to move your cursor to a long distance

(5) With further additions, can even help to monitor your health.

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LIST OF FIGURES

Fig No Figure Name Page

1.1 The BlueEye system with the camera(s) 9

mounted on top and the display integrated

into the table surface.

3.1 Emotional Mouse 11

3.2 Bright and dark pupil images 12

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CONTENTS

Chapter Page No.

Title Page 1

Acknowledgement 2

Abstract 3

Tables and figures 4

1. Introduction 6

1.1 Aim 6

1.2 Objective 7

2. Definition of BlueEyes Technology 8

3. Technologies used 10

3.1 Emotion Mouse 10

3.2 MAGIC 11

3.3 Artificial Intelligent Speech Recognition 13

3.4 SUITOR 16

4 System Overview 18

4.1 Parts of BlueEye system 18

4.1.1 DAU

4.2.2 CSU

5 Applications and Future Scope 23

7. References 25

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CHAPTER 1

INTRODUCTION

Is it possible to create a computer which can interact with us as we

interact each other? For example imagine in a fine morning you walk on

to your computer room and switch on your computer, and then it tells you

“Hey friend, good morning you seem to be a bad mood today. And then it

opens your mailbox and shows you some of the mails and tries to cheer

you. It seems to be a fiction, but it will be the life lead by “BLUE EYES”

in the very near future. The basic idea behind this technology is to give

the computer the human power. We all have some perceptual abilities.

That is we can understand each others feelings. For example we can

understand ones emotional state by analyzing his facial expression. If we

add these perceptual abilities of human to computers would enable

computers to work together with human beings as intimate partners. The

“BLUE EYES” technology aims at creating computational machines that

have perceptual and sensory ability like those of human beings.

Blue Eyes uses sensing technology to identify a user's actions and to

extract key information. This information is then analyzed to determine

the user's physical, emotional, or informational state, which in turn can be

used to help make the user more productive by performing expected

actions or by providing expected information. For example, in future a

Blue Eyes-enabled television could become active when the user makes

eye contact, at which point the user could then tell the television to "turn

on". This paper is about the hardware, software, benefits and

interconnection of various parts involved in the “blue eye” technology.

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1.1 Aim

The aim of this seminar is to study about BlueEyes Technologyand

have a deep insight of latest developments taking place in this field.

1.2 Objectives

• Research current methods to implement BlueEyes technology.

• Research into latest developments in this area.

• To realise the applications of BlueEyes technology.

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CHAPTER 2

1.WHAT IS BLUEEYES TECHNOLOGY?

Animal survival depends on highly developed sensory abilities. Likewise,

human cognition depends on highly developed abilities to perceive,

integrate, and interpret visual, auditory, and touch information. Without a

doubt, computers would be much more powerful if they had even a small

fraction of the perceptual ability of animals or humans. Adding such

perceptual abilities to computers would enable computers and humans to

work together more as partners. Toward this end, the Blue Eyes aims at

creating computational devices with the sort of perceptual abilities that

people take for granted Blue eyes is being developed by the team of

Poznan University of Technology& Microsoft. It makes use of the “blue

tooth technology “developed by Ericsson.

BlueEyes is the name of a human recognition venture initiated by

IBM to allow people to interact with computers in a more natural manner.

The technology aims to enable devices to recognize and use natural input,

such as facial expressions. The initial developments of this project

include scroll mice and other input devices that sense the user's pulse,

monitor his or her facial expressions, and the movement of

his or her eyelids. BlueEyes technology aims at creating computational

machines that have perceptual and sensory ability.It uses cameras and

microphones to identify user actions and emotions. BLUE in the term

stands for Bluetooth, which enables reliable wireless communication and

EYES has been used because the eye movement enables us to obtain a lot

of interesting and important information. It doesn’t predict nor interfere

with operator’s thoughts nor can it force directly the operator to work.

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Figure 1.1 The BlueEye systems with the camera(s) mounted on top and

the display integrated into the table surface.

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CHAPTER 3

2.TECHNOLOGIES USED

To implement BlueEyes technology four main technologies are used:

Emotion Mouse

Manual And Gaze Input Cascaded (MAGIC)

Artificial Intelligent Speech Recognition

Simple User Interest Tracker (SUITOR)

3.1 Emotion Mouse

By matching a person’s emotional state and the context of the

expressed emotion, over a period of time the person’s personality is being

exhibited. Therefore, by giving the computer a longitudinal

understanding of the emotional state of its user, the computer could adapt

a working style which fits with its user’s personality. The result of this

collaboration could increase productivity for the user. One way of gaining

information from a user non-intrusively is by video. Cameras have been

used to detect a person’s emotional state (Johnson, 1999). We have

explored gaining information through touch. One obvious place to put

sensors is on the mouse. Through observing normal computer usage

(creating and editing documents and surfing the web), people spend

approximately 1/3 of their total computer time touching their input

device. Because of the incredible amount of time spent touching an input

device, we will explore the possibility of detecting emotion through

touch.

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Figure 3.1 Emotional Mouse

3.2 Manual and Gaze Input Cascaded (MAGIC)

This is a way of providing input to the computer through eye gaze.

With such an approach , pointing on screen appears to the user a manual

task, used for fine manipulations and selections. In this a large portion of

the cursor movement is eliminated by warping the cursor to the eye gaze

area, which encompasses the target. This technique has many advantages

including reduced physical effort and fatigue, greater accuracy and

naturalness and faster speed. Here we have limited to the most advanced

technique of MAGIC i.e. the IBM Alamaden eye tracker.

3.2.1 The IBM Almaden Eye Tracker

This system is much more compact and reliable. However, it is still

not robust enough for a variety of people with different eye

characteristics, such as pupil brightness and correction glasses. Available

commercial systems, such as those made by ISCAN Incorporated, LC

Technologies, and Applied Science Laboratories (ASL), rely on a single

light source that is positioned either off the camera axis in the case of the

ISCANETL-400 systems, or on-axis in the case of the LCT and the ASL

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E504 systems. Illumination from an off-axis source (or ambient

illumination) generates a dark pupil image.

When the light source is placed on-axis with the camera optical

axis, the camera is able to detect the light reflected from the interior of

the eye, and the image of the pupil appears bright

Figure 3.2: Bright (left) and dark (right) pupil images resulting from on-

and off-axis illumination. The glints, or corneal reflections, from the on-

and off-axis light sources can be easily identified as the bright points in

the iris.

Almaden system uses two near infrared (IR) time multiplexed lightsources, composed of two sets of IR LED's, which were synchronized

with the camera frame rate. One light source is placed very close to the

camera's optical axis and is synchronized with the even frames. Odd

frames are synchronized with the second light source, positioned off axis.

The two light sources are calibrated to provide approximately equivalent

whole-scene illumination. Pupil detection is realized by means of

subtracting the dark pupil image from the bright pupil image. After

thresholding the difference, the largest connected component is identified

as the pupil. This technique significantly increases the robustness and

reliability of the eye tracking system.

Once the pupil has been detected, the corneal reflection (the glint reflected

from the surface of the cornea due to one of the light sources) is

determined from the dark pupil image. The reflection is then used to

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estimate the user's point of gaze in terms of the screen coordinates where

the user is looking at. The estimation of the user's gaze requires an initial

calibration procedure.

3.3

Artificial Intelligent Speech Recognition

It is important to consider the environment in which the speech

recognition system has to work. The grammar used by the speaker and

accepted by the system, noise level, noise type, position of the

microphone, and speed and manner of the user’s speech are some factors

that may affect the quality of speech recognition .When you dial the

telephone number of a big company, you are likely to hear the sonorous

voice of a cultured lady who responds to your call with great courtesy

saying “Welcome to company X. Please give me the extension number

you want”. You pronounce the extension number, your name, and the

name of person you want to contact. If the called person accepts the call,

the connection is given quickly. This is artificial intelligence where an

automatic call- handling system is used without employing any telephone

operator.

3.3.1 The Technology

Artificial intelligence (AI) involves two basic ideas. First, it involves

studying the thought processes of human beings. Second, it deals with

representing those processes via machines (like computers, robots, etc).

AI is behavior of a machine, which, if performed by a human being,

would be called intelligent. It makes machines smarter and more useful,

and is less expensive than natural intelligence. Natural language

processing (NLP) refers to artificial intelligence methods of

communicating with a computer in a natural language like English. Themain objective of a NLP program is to understand input and initiate

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action. The input words are scanned and matched against internally stored

known words. Identification of a key word causes some action to be

taken. In this way, one can communicate with the computer in one’s

language. No special commands or computer language are required.

There is no need to enter programs in a special language for creating

software.

3.3.2 Speech Recognition

The user speaks to the computer through a microphone with a simple

system that may contain a minimum of three filters. The more the number

of filters used, the higher the probability of accurate recognition.

Presently, switched capacitor digital filters are used because these can be

custom-built in integrated circuit form. These are smaller and cheaper

than active filters using operational amplifiers. The filter output is then

fed to the ADC to translate the analogue signal into digital word. The

ADC samples the filter outputs many times a second. Each sample

represents different amplitude of the signal. Evenly spaced vertical lines

represent the amplitude of the audio filter output at the instant of

sampling. Each value is then converted to a binary number proportional

to the amplitude of the sample. A central processor unit (CPU) controls

the input circuits that are fed by the ADCS. A large RAM (random access

memory) stores all the digital values in a buffer area. This digital

information, representing the spoken word, is now accessed by the CPU

to process it further. The normal speech has a frequency range of 200 Hz

to 7 kHz. Recognizing a telephone call is more difficult as it has

bandwidth limitation of 300 Hz to3.3 kHz.

As explained earlier, the spoken words are processed by the filters

and ADCs. The binary representation of each of these words becomes a

template or standard, against which the future words are compared. These

templates are stored in the memory. Once the storing process is

completed, the system can go into its active mode and is capable of

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identifying spoken words. As each word is spoken, it is converted into

binary equivalent and stored in RAM. The computer then starts searching

and compares the binary input pattern with the templates. t is to be noted

that even if the same speaker talks the same text, there are always slight

variations in amplitude or loudness of the signal, pitch, frequency

difference, time gap, etc. Due to this reason, there is never a perfect

match between the template and binary input word. The pattern matching

process therefore uses statistical techniques and is designed to look for

the best word.

The values of binary input words are subtracted from the

corresponding values in the templates. If both the values are same, the

difference is zero and there is perfect match. If not, the subtraction

produces some difference or error. The smaller the error, the better the

match. When the best match occurs, the word is identified and displayed

on the screen or used in some other manner. The search process takes a

considerable amount of time, as the CPU has to make many comparisons

before recognition occurs. This necessitates use of very high-speed processors. A large RAM is also required as even though a spoken word

may last only a few hundred milliseconds, but the same is translated into

many thousands of digital words. It is important to note that alignment of

words and templates are to be matched correctly in time, before

computing the similarity score. This process, termed as dynamic time

warping, recognizes that different speakers pronounce the same words at

different speeds as well as elongate different parts of the same word. This

is important for the speaker-independent recognizers.

3.3.3 Applications

One of the main benefits of speech recognition system is that it lets user

do other works simultaneously. The user can concentrate on observation

and manual operations, and still control the machinery by voice input

commands. Another major application of speech processing is in military

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operations. Voice control of weapons is an example. With reliable speech

recognition equipment, pilots can give commands and information to the

computers by simply speaking into their microphones—they don’t have

to use their hands for this purpose. Another good example is a radiologist

scanning hundreds of X- rays, ultrasonograms, CT scans and

simultaneously dictating conclusions to a speech recognition system

connected to word processors. The radiologist can focus his attention on

the images rather than writing the text. Voice recognition could also be

used on computers for making airline and hotel reservations. A user

requires simply to state his needs, make reservation, cancel a reservation,

or make enquiries about schedule

3.4 The Simple User Interest Tracker (SUITOR)

Computers would have been much more powerful, had they

gained perceptual and sensory abilities of the living beings on the earth.

What needs to be delivered is an intimate relationship between the

computers and the humans. SUITOR is a revolutionary approach in this

direction.

By observing the Webpage the subject is browsing, the SUITOR

can help by fetching more information on the desktop. By Simply

noticing where the user ‘s eye focus on the computer screen , the

SUITOR can be more precise in determining his topic of interest. It can

even deliver relevant information to a handheld device. The success lies

in how much the SUITOR can be intimate to the user. IBM’s BlueEyes

research concentrated on if we can explore non verbal cues tp create more

effective user interface.

One such cue is gaze-the direction in which a person is looking.

IBM’s research has incorporated gaze-tracking technology into two

prototypes. One, called SUITOR, fills a scrolling ticker on a computer

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screen with information related to users task. SUITOR knows where you

are looking, what applications you are running and what page you may be

browsing. For example if one is reading the headline of a story, it pops up

the story in the browser window. If he reads story the computer adds

related stories to the ticker.

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connection, buffers incoming sensor data, performs on-line data analysis,

records the conclusions for further exploration and provides visualization

interface.

4.1.2.1 CSU Components

Connection Manager – main task to perform low-level blue tooth

communication.

Data Analysis Module – performs the analysis of the raw sensor

data in order. to obtain information about operator’s physiological

condition

Data Logger Module – provides support for storing the monitored

data.

Visualization Module – provides user interface for the

supervisors.

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CHAPTER 5

4.APPLICATIONS

1. Computers Can Anticipate User’s Wants

BlueEyes is developing ways for computers to anticipate users'

wants by gathering video data on eye movement and facial

expression. Your gaze might rest on a Web site heading, for example,

and that would prompt your computer to find similar links and to call

them up in a new window. But the first practical use for the research

turns out to be snooping on shoppers.

BlueEyes software makes sense of what the cameras see to answer key questions for retailers, including, How many shoppers ignored a

promotion? How many stopped? How long did they stay? Did their

faces register boredom or delight? How many reached for the item

and put it in their shopping carts? BlueEyes works by tracking pupil,

eyebrow and mouth movement. When monitoring pupils, the system

uses a camera and two infrared light sources placed inside the product

display. One light source is aligned with the camera's focus; the other

is slightly off axis. When the eye looks into the camera-aligned light,

the pupil appears bright to the sensor, and the software registers thecustomer's attention. This is way it captures the person's income and

buying preferences. BlueEyes is actively been incorporated in some

of the leading retail outlets.

2. In Automobile Industry

Another application would be in the automobile industry. By

simply touching a computer input device such as a mouse, the

computer system is designed to be able to determine a person'semotional state. For cars, it could be useful to help with critical

decisions like:

"I know you want to get into the fast lane, but I'm afraid I can't do

that. You are

too upset right now" and therefore assist in driving safely.

3. Face-responsive Displays" and "Perceptive Environments

Current interfaces between computers and humans can present

information vividly, but have no sense of whether that information is

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ever viewed or understood. In contrast, new real-time computer vision

techniques for perceiving people allows us to create "Face-responsive

Displays" and "Perceptive Environments", which can sense and

respond to users that are viewing them. Using stereo-vision

techniques, we are able to detect, track, and identify users robustlyand in real time. This information can make spoken language

interface more robust, by selecting the acoustic information from a

visually-localized source. Environments can become aware of how

many people are present, what activity is occurring, and therefore

what display or messaging modalities are most appropriate to use in

the current situation. The results of our research will allow the

interface between computers and human users to become more

natural and intuitive.

4. Video Games

We could see its use in video games where, it could give

individual challenges to customers playing video games. Typically

targeting commercial business.

The integration of children's toys, technologies and computers is

enabling new play experiences that were not commercially feasible

until recently. The Intel Play QX3 Computer Microscope, the

Me2Cam with Fun Fair, and the Computer Sound Morpher are

commercially available smart toy products developed by the Intel

Smart Toy Lab in . One theme that is common across these PC-

connected toys is that users interact with them using a combination of

visual, audible and tactile input & output modalities. The presentation

will provide an overview of the interaction design of these products

and pose some unique challenges faced by designers and engineers of

such experiences targeted at novice computer

users, namely young children.

5. Less Explicit Communication

The familiar and useful come from things we recognize. Many of

our favorite things' appearance communicate their use; they show the

change in their value though patina. As technologists we are now

poised to imagine a world where computing objects communicate

with us in-situ; where we are. We use our looks, feelings, and actions

to give the computer the experience it needs to work with us.

Keyboards and mice will not continue to dominate computer user

interfaces. Keyboard input will be replaced in large measure bysystems that know what we want and require less explicit

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communication. Sensors are gaining fidelity and ubiquity to record

presence and actions; sensors will notice when we enter a space, sit

down, lie down, pump iron, etc. Pervasive infrastructure is recording

it. This talk will cover projects from the Context Aware Computing

Group at MIT Media Lab.

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CHAPTER 7

6. REFRENCES

1. www.alphaworks.ibm.com/awap.nsf/alltype/86ECE8569056DDC7

88256AEE007A9702

2. www.cse.ogi.edu/CHCC/Series/text2001.html

3. BlueEyes Technology, Computer Edge, Oct.2002, pages 23-27.

4. BlueEyes Technology and Applications, Business Solutions, Nov

2001,pages 95-99.

5. www.cs.put.poznan.com

6. www.whitepapers.com

7. www.ibmresearchcenter.com

8. www.almaden.ibm.com

9. Carpenter R. H. S., Movements of the eyes, 2nd edition, Pion

Limited, 1988, London.

10. Quinlan J. R., C4.5 programs for machine learning, Morgan

Kaufmann Publishers, 1993, San Mateo, California.

11. http://www.articlesbase.com/networks-articles/blue-eyes-

monitoring-human-operator-system-420263.html

12. Milgram, P. and Kishino, F. (1994) A Taxonomy of Mixed Reality

Visual Displays, IEICE Transactions on Information Systems,

1321-1329.

http://www.cse.ogi.edu/CHCC/Series/text2001.html

http://www.cs.put.poznan.com/

http://www.whitepapers.com/

http://www.ibmresearchcenter.com/

http://www.almaden.ibm.com/

http://www.articlesbase.com/networks-articles/blue-eyes-monitoring-human-operator-system-420263.html


http://www.cs.put.poznan.com/

http://www.whitepapers.com/

http://www.ibmresearchcenter.com/

http://www.almaden.ibm.com/



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