Description

ABSTRACT

Eye ball tracking system is assistant system to the patients who are not able to the voluntary works of the daily life. To communicate to the real world eye ball tracking will be useful. Patients who can control their eyes they can communicate to the people in the real world. In this project we are proposing one algorithm to identify and track the eye ball of our eye. A real time data is captured via webcam that transfers data serially to the system of matlab.   Then a sequential image processing scheme will segment the iris of the eye and calculate center there one control signal will be generated with the help of reference axis. Then we can track the eyes with help of the signals.

DEMO VIDEO

INTRODUCTION

Communication between humans is among the greatest tool that they used to maintain their sustenance in this world. Apart from several languages constituting words that are evolved since the beginning of mankind, a universally known non-verbal expression still holds a noticeable weight in the eyes of humans. It is a common observation that human eyes suffices the need to express thousands words that convey huge emotions and feelings. In-spite of this, there are cases when humans suffer from a disease which makes them incapable of moving any part of their body except their eyes. At that stage eye movement is very critical in order for the patient to communicate with the real-world and its surroundings.  Researchers working in the field of neuroscience utilize eye movement to read how human’s visual information processes. Clinicians in the field of psychology, psychiatry and psycholinguistics, use eye tracking systems for collecting data discretely and accurately. On-screen vision studies are conducted in the field of ophthalmology, furthering our understanding of the human eye and help developing new approaches for the diagnosis of disorders.

EXISTING SYSTEM

Previously we are using feature matching algorithm to identify the eye in the plane. But those things will not work accurately while tracking the eyes. The algorithm which we are using in the existing system is better to identify the eyeball in the system by using webcam but we cant track accurate object sometimes it will not work exactly. Here we are going with a proposed algorithm for tracking system

PROPOSED METHOD

Particularly in the proposed system we are using viola Jones algorithm to track the eyes. The algorithm will work as well as identification and tracking the object with same features of which we had given in the database system. Mainly it will concentrate on how to extract the feature from a face in real time environment.

BLOCK DIAGRAM

ADVANTAGES

• Eye ball identification of and creating boundary boxes particularly
• Using real time application of  web camera

APPLICATIONS

• Detecting driver drowsiness
• Object tracking applications

HARDWARE REQUIREMENTS

• Logitech quick cam pro 9000
• Personal computer

SOFTWARE REQUIREMENTS

• Matlab 14 And above versions

MATLAB GUI FOR EYE TRACKING

CONCLUSION

This project will track eyes in real time from a web camera using viola Jones face detection algorithm. Here we are using mat lab implementation for track the eyes. The main advantage of mat lab is we can access the web camera with image acquisition tool box and face detection algorithm. The hardware requirement for this project is simple one pc(personal computer) and web camera. The pc which we are using in this project will require minimum 2GB ram and dual core processer operation of Intel.

REFERENCES

[1] Mitsumoto H, Chad DA, Pioro EP. Amyotrophic lateral sclerosis. Philadelphia, PA: F.A. Davis Company; 1998.

[2] Ziad O. Abu-Faraj, Maya J. Mashaalany, Habib C. Bou Sleiman, Jean-Louis D. Heneine, and Waleed M. Al Katergi,“Design and Development of a Low-Cost Eye Tracking System for the Rehabilitation of the Completely Locked-In Patient” Proceedings of the 28th IEEE EMBS Annual International Conference New York City, USA, Aug 30-Sept 3, 2006.

[3] Chern-Sheng Lin, Chien-Wa Ho, Wen-Chen Chen, Chuang-Chien Chiu, Mau-Shiun Yeh, ”Powered wheelchair controlled by eyetracking system,” Optica Applicata 2006(Vol.36), No.2-3, pp. 401- 412

[4] Andrew T. Dchowski, “A breadth-first survey of eye-tracking applications”, Behavior Research Methods, Instruments, & Computers 2002, 34 (4), 455-470.

[5] Betul Sahin, Barbara Lamory, Xavier Levecq, Fabrice Harms and Chris Dainty, “Adaptive optics with pupil tracking for high resolution retinal imaging”, 1 February 2012 / Vol. 3, No. 2 / BIOMEDICAL OPTICS EXPRESS 225.

[6] J.A. Nagel, C. Kutschker, C. Beck, U. Gengenbach, H. Guth, G. Bretthauer, “Comparison of different algorithms for robust detection of pupils in real-time eye tracking experiments.”, Biomed Tech 2013; 58 (Suppl. 1) © 2013 by Walter de Gruyter, Berlin.

[7] Aji Joy, Ajith P Somaraj, Amal Joe, Muhammed Shafi, Nidheesh T M, “Ball Tracking Robot Using Image Processing and Range Detection”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, Issue 3, March 2014.