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Real Time Gaze Tracking
and Applications
-By Akshay B.Kamble-2013BCS075Under Guidance Of:
Prof.Dr.B.F.Momin
Prof.,Computer Science & Engg.
Dept,WCE
Mr.V.M.Banahatti
Senior Researcher at TRDDC,Pune
Project At- Tata Research Development and Design
Centre
Problem Statement
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2
Create real time gaze tracking application which will use for different security aspect.
-Pupil Detection.
-Handle screen by gaze.
-Calibrate data
3Objectives And Scope of Project
Why Choose this project????
Raising technology in technical Era and Research
domain.
4
Motivation
“
Human psychology and eye-mind
hypothesis,that amount of time spends
thinking about an Object is directly
proportional to time spent looking at it.
5
Applications
» Gaming world.
» Security Domain.
» Medical Field.
-We focus On security domain.
6
CONCEPT
7
BIG
-Authentication access by
gaze
-Data Monitoring/Calibrating
-Avoid Shoulder Surfing
8
Authentication access By gaze
The process or action of proving or showing something to be true,
genuine, or valid.
The process or action of verifying the identity of a user or process.
9
Data Monitoring
-Sensitive Data monitorate and calibrate by user’s.
10
Shoulder Surfing
The of spying on the user’s of cash dispensing machines or any other
device in order to obtain their personal identification number , password
, sensitive data ,etc.
11
Software’s
-Javascript
-Python
-Android
-OpenCV
12
EXPLAIN IDEAS
Matching Device
Coordinates
Accurate Pupil
Detection
Data Calibration
13
Algorithms: 14
-SURF -(Speed Up Robust
Feature).
-HaarCascade Algorithms
-RANSAC Algorithms.
-HeatMap algorithm.
Algorithms: 15
SURF(SpeededUp Robust Featrures):
1.Detection.
2.Description.
3.Matching.
Algorithm 16
RANSAC(RANdom SAmple Consensus):
-adopted by the computer vision community.
-esampling technique that generates candidate solutions by using
the minimum number observations (data points) required to estimate the
underlying model parameter.
Algorithm: 17
1:Select randomly the minimum number of points required to determine the model
parameters.
2Solve for the parameters of the model.
3:Determine how many points from the set of all points fit with a predefined toler-
ance.
4:If the fraction of the number of inliers over the total number points in the set
exceeds a predefined threshold τ, re-estimate the model parameters using all the
identified inliers and terminate.
5:Otherwise, repeat steps 1 through 4 (maximum of
N times).
Implementation: 18
*Javascript:
-Implementation of gaze tracking System.
-clmtracker.
-Regression & Calibration.
-Tracker
Heatmap: 19
Graphical Password Authentication System: 20
-Using gaze ,we implement the graphical Password authentication System.
#Testing & analysis:
-on 16 people ,I tested this project.
-almost 95% result is correct.
Learning
-Agile Methodology
-Open Source vision
techniques.
-Human-Computer
Interaction(HCI).
-Security Constraint
21
22
Agile Methodology
Place your screenshot here
23
Current State Of Project
-able to capture area
according to gaze.
-Using heatmap we
can Calibrate data.
-We developed
graphical password
authentication
System.
24
Future Scope:
-Medical Field.
-Gaming Era
25
SOUPS(Symposium On Usable Privacy and Security):
-This conference eld in June 2017, we will going to
publish this paper after completion of remaining factor.
Place your screenshot here
26
Conclusion
“Prevention is always
better than cure” as
D.Erasmus said.
-Provide security using
gaze technology.
27
References
-V. a. Gevers, "Accurate Eye Center Location and Tracking Using Isophote
Curvature," IEEE Conference on Computer Vision and Pattern Recognition,
2008
-Institute for Neuro- and Bioinformatics, University of L¨ubeck, Ratzeburger
Allee 160, D-23538 L¨ubeck, Germany,"ACCURATE EYE CENTRE LOCALISATION
BY MEANS OF
GRADIENTS",2013
-Wen Hao Lui,"Real-time Webcam Gaze-tracking",2014.
-Alexandra Papoutsaki,"ScalableWebcam Eye Tracking Using User
Interactions",2014.
Any questions?
28THANKS!

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Real Time Eye Tracking and Application

  • 1. Real Time Gaze Tracking and Applications -By Akshay B.Kamble-2013BCS075Under Guidance Of: Prof.Dr.B.F.Momin Prof.,Computer Science & Engg. Dept,WCE Mr.V.M.Banahatti Senior Researcher at TRDDC,Pune Project At- Tata Research Development and Design Centre
  • 2. Problem Statement More info on how to use this template at www.slidescarnival.com/help-use-presentation-template This template is free to use under Creative Commons Attribution license. You can keep the Credits slide or mention SlidesCarnival and other resources used in a slide footer. 2 Create real time gaze tracking application which will use for different security aspect.
  • 3. -Pupil Detection. -Handle screen by gaze. -Calibrate data 3Objectives And Scope of Project
  • 4. Why Choose this project???? Raising technology in technical Era and Research domain. 4 Motivation
  • 5. “ Human psychology and eye-mind hypothesis,that amount of time spends thinking about an Object is directly proportional to time spent looking at it. 5
  • 6. Applications » Gaming world. » Security Domain. » Medical Field. -We focus On security domain. 6
  • 8. -Authentication access by gaze -Data Monitoring/Calibrating -Avoid Shoulder Surfing 8
  • 9. Authentication access By gaze The process or action of proving or showing something to be true, genuine, or valid. The process or action of verifying the identity of a user or process. 9
  • 10. Data Monitoring -Sensitive Data monitorate and calibrate by user’s. 10
  • 11. Shoulder Surfing The of spying on the user’s of cash dispensing machines or any other device in order to obtain their personal identification number , password , sensitive data ,etc. 11
  • 13. EXPLAIN IDEAS Matching Device Coordinates Accurate Pupil Detection Data Calibration 13
  • 14. Algorithms: 14 -SURF -(Speed Up Robust Feature). -HaarCascade Algorithms -RANSAC Algorithms. -HeatMap algorithm.
  • 15. Algorithms: 15 SURF(SpeededUp Robust Featrures): 1.Detection. 2.Description. 3.Matching.
  • 16. Algorithm 16 RANSAC(RANdom SAmple Consensus): -adopted by the computer vision community. -esampling technique that generates candidate solutions by using the minimum number observations (data points) required to estimate the underlying model parameter.
  • 17. Algorithm: 17 1:Select randomly the minimum number of points required to determine the model parameters. 2Solve for the parameters of the model. 3:Determine how many points from the set of all points fit with a predefined toler- ance. 4:If the fraction of the number of inliers over the total number points in the set exceeds a predefined threshold τ, re-estimate the model parameters using all the identified inliers and terminate. 5:Otherwise, repeat steps 1 through 4 (maximum of N times).
  • 18. Implementation: 18 *Javascript: -Implementation of gaze tracking System. -clmtracker. -Regression & Calibration. -Tracker
  • 20. Graphical Password Authentication System: 20 -Using gaze ,we implement the graphical Password authentication System. #Testing & analysis: -on 16 people ,I tested this project. -almost 95% result is correct.
  • 21. Learning -Agile Methodology -Open Source vision techniques. -Human-Computer Interaction(HCI). -Security Constraint 21
  • 23. Place your screenshot here 23 Current State Of Project -able to capture area according to gaze. -Using heatmap we can Calibrate data. -We developed graphical password authentication System.
  • 25. 25 SOUPS(Symposium On Usable Privacy and Security): -This conference eld in June 2017, we will going to publish this paper after completion of remaining factor.
  • 26. Place your screenshot here 26 Conclusion “Prevention is always better than cure” as D.Erasmus said. -Provide security using gaze technology.
  • 27. 27 References -V. a. Gevers, "Accurate Eye Center Location and Tracking Using Isophote Curvature," IEEE Conference on Computer Vision and Pattern Recognition, 2008 -Institute for Neuro- and Bioinformatics, University of L¨ubeck, Ratzeburger Allee 160, D-23538 L¨ubeck, Germany,"ACCURATE EYE CENTRE LOCALISATION BY MEANS OF GRADIENTS",2013 -Wen Hao Lui,"Real-time Webcam Gaze-tracking",2014. -Alexandra Papoutsaki,"ScalableWebcam Eye Tracking Using User Interactions",2014.