presentation .

1. Presented by,
Shehin P M
S7 ECE
Roll No :52
1

2. CONTENTS
 Abstract
 Introduction
 What is Blue Eyes?
 Why Blue Eyes?
 Hardware
 Software
 Technologies used
 Advantages and disadvantages
 Applications
 Summary
 References 2

3. ABSTRACT
‘Blue Eyes’ is the technology to make computers sense and
understand human behavior and feelings and react in the
proper ways through gadgets.The machine can understand
what a user wants, where he is looking at and realize his
physical or emotional states. Blue eyes uses sensing
technology to identify a user’s actions and to extract key
information. The information is then analyzed to determine
user’s physical, emotional or informational state which in turn
can be used to make the user more productive by performing
expected actions or by providing expected information.
Adding the perceptual abilities of human to computers, would
enable computers to interact and work together with human
beings as intimate partners.
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4. INTRODUCTION
 BLUE EYES technology started at IBM's Almaden
Research Centre in USA.
 Gives computers highly developed abilities to
perceive, integrate and interpret visual, auditory and
touch information.
 Aims at creating computational machines that have
perceptual and sensory ability.
Monitors and records operator’s conscious brain
involvement .
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5. WHAT IS BLUE EYES??
 Provides technical means for monitoring and recording
human-operator's physiological condition.
 BLUE-Bluetooth
 EYES-eye moment enables to obtain lot of information.
 key features are:
• Visual attention monitoring.
• Physiological condition monitoring.
• Operator's position detection.
• Wireless data acquisition.
• Real-time user-defined alarm triggering. 5

6. • To avoid and reduce human limitation such as:
 Tiredness
 Oversight
 Mental illness, etc
• Monitoring of conscious brain involvement
(automation, long driving)
• To built a machine that can understand your
emotions.
• Verify your identity, feels your presence and interact
with you.
Why Blue Eyes??
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7. HARDWARE
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8. HARDWARE
 Monitors status of operator’s visual attention.
 Checks parameters like heart beat rate and blood
oxygenation.
 Triggers user defined alarms.
 Mobile device is integrated with bluetooth module.
 Adequate user profiles provide necessary data
personalization.
 Data security.
 Consists of
• Mobile measuring device(DAU)
• Central system unit 8

9. Data Acquistion Unit
9

10. Contd.
• Fetch physiological data from sensor.
• Send it to central system for processing.
• Manage wireless bluetooth connection.
• Personal ID cards and PIN codes provide operator’s
authorization.
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11. Contd.
DAU comprises of several hardware modules
 Atmel 89C52 microcontroller - system core
 Bluetooth module based on ROK101008
HD44780 - small LCD display
 24C16 - I2C EEPROM (on a removable ID card)
 MC145483 – 13bit PCM codec
 Jazz Multisensor interface
 Beeper and LED indicators.
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12. JAZZ Multisensor
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13. Contd..
• Supplies raw physical data regarding eye
position,level of blood oxygenation.
• Eye position measuring - direct infrared oculography
• Oxy- and deoxyheamoglobin measurement.
• Two axial accelerometer
• Ambient light sensor
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14. Central System Unit
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15. Central System Unit
 Maintains BT connections.
 Buffers incoming sensor data.
 Performs on-line data analysis.
 Records the conclusion for further exploration.
 Provides visualization interface.
 PCM codec for voice data transmission.
 Module is interfaced to a PC using a parallel,serial
and USB cable.
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16. SOFTWARE
• Performs real time buffering of incoming data.
• Real time physiological data analysis.
• Alarm triggering
• System core facilitates transfer flow between system
modules.
• Consists of four modules.
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17. 17

18. CONNECTION MANAGER MODULE
 Manages wireless communication between mobile
DAU and central system.
 Connection Manager handles:
• Communication with CSU hardware
• Searching for new devices in covered
range
• Establishing Bluetooth connections
• Connection authentication
• Incoming data buffering
• Sending alerts
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19. DATA ANALYSIS MODULE
 Analysis of raw sensor data.
 Supervises working operators.
 Large number of smaller analyzers extracting
information.
 The most important analyzers are:
• Saccade detector - monitors eye movements in order
to determine the level of operator's visual attention
• Pulse rate analyzer - uses blood oxygenation signal to
compute operator's pulse rate
• Custom analyzers - recognize other behaviors than
those which are built-in the system.
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20. DATA LOGGER MODULE
• The raw or processed physiological data, alerts and
operator's voice are stored.
• A Voice Data Acquisition module delivers the voice
data.
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21. VISUALIZATION MODULE
 Provides a user interface for the supervisors.
 Enables to watch each of the working operator’s
physiological condition.
 Incoming alarm messages are instantly signalled.
 Can be set in an offline mode, where all data is
fetched from database.
 Reconstruct course of selected operator’s duty.
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22. TECHNOLOGIES USED
• Emotion Mouse.
• Manual And Gaze Input Cascaded (MAGIC).
• Artificial Intelligent Speech Recognition.
• Simple User Interest Tracker (SUITOR).
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23. Emotion Mouse
 Non-invasive method for gaining user information
through touch.
 Measure heart rate, temperature, galvanic skin
response and minute bodily movements
 Matches with six emotional states: happiness,
surprise, anger, fear,sadness and disgust.
 Includes different sensors including pressure
sensor,heart beat sensor,temperature sensor.
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25. Manual and Gage Input Cascading
(MAGIC)
• pointing appears to
user to be a manual task
• used for fine
manipulation and
selection.
• Webcam is used to
determine glints and
pupils of user.
• Wrap cursor to every
new object cursor looks
at.
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26. SPEECH RECOGNITION
• user speaks to computer through a microphone.
• Switched capacitor digital filters are used.
• ADC samples filter outputs.
• Each sample represents different amplitude of signal.
• Converted to binary number proportional to
amplitude of sample.
• Binary repesentation of words become
standards/templates and stored in memory.
• Input words are scanned and matched .
• When best match occurs,word is identified and
displayed on screen.
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27. The Simple User Interest Tracker
(SUITOR)
• Fetches more information at desktop.
• Notice where the user’s eyes focus on the screen.
• Precise in determining user’s topic of interest.
• Deliver relevant information to a handheld device.
• Eg-If reading headline ,pops up story in browser
window.
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28. Advantages and Disadvantages
Advantages
 Prevention from dangerous incidents.
 The reconstruction of the course of operator’s work.
 Minimization of
ecological consequences.
financial loss.
a threat to a human life.
Disadvantages
 Requires Miniaturization.
 Not 100% accurate.
 Expensive
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29. Applications
• Working environment requiring permanent attentions.
• At power plant control rooms.
• At captain bridges.
• At flight control centers.
• Professional Drivers.
• In automobile industry.
• In video games.
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30. SUMMARY
• Provide more delicate and user friendly facilities in
computing devices.
• Gap between the electronic and physical world is
reduced.
• Computers can be run using implicit commands
instead of explicit commands.
• In future, ordinary household devices- such as
television may be able to do their jobs when we look
at them and speak to them
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31. REFERENCES
[1] Blue eyes technology by Himanshu Sharma and Gaurav
Rathee in International Journal of Computer Science and
Management Research(2013).
[2] Blue eyes technology by Mizna Rehman 2013.
[3] Psychologist World, Eye Reading Language (Body
Language), July2013, www. psychologistworld.
com/bodylanguage/ eyes. php.
[4] McDuff D., Kaliouby R., Senechal T., Amr M., Cohn J.,
Picard R. W., "Affective-MIT Facial Expression Dataset
(AMFED): Naturalistic and Spontaneous Facial Expressions
Collected In-The-Wild. ", The 2013 IEEE Computer Society
Conference on Computer Vision and Pattern Recognition
Workshops (CVPRW'10), Portland, OR, USA, June 2013.
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32. [5] Amir Aly, Adriana Tapus, "Towards an Online Fuzzy Modeling For
Human Internal States Detection", 2012 12th Internal Conference On
Control, Automation Robotics and Vision Guangzhou, China, 5-7th
December 2012(ICARCV2012)
[6] Renu Nagpal, Pooja Nagpal, Sumeet Kaur, "Hybrid Technique for
Human Face Emotion Detection", International Journal of Advanced
Computer Science and Applications Vol. 1 No6, December 2010.
[7] Suvam Chatterjee, Haoshi, "A Novel Neuro Fuzzy Approach to
Human Emotion Determination", Digital Image Computing
Techniques and Application (DICIA), 2010 International Conference.
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