Ali, Md. HaiderHasan, SakibTamim, Md. Tahsin AlamRobin, S. M. Tarequl HasanTasnim, SadiaMahmud, Shah Tanvir2017-01-302017-01-3020162016ID 12301003ID 12301022ID 12301013ID 14101265ID 12321054http://hdl.handle.net/10361/7711Cataloged from PDF version of thesis report.Includes bibliographical references (page 25)This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.For people with mobility disabilities, communicating via smartphone is often frustrating, and require constant assistance. Among the diseases, only Parkinsons disease alone a↵ects up to 10 million people worldwide[1]. Especially, people having hand tremor, have major issues using mobile phones. To solve this, we want to implement a mobile application that will enable users to operate the mobile device touch-free. Most of the current eye tracking solutions use expensive hardware, but our proposed system will not require any additional hardware, it will use mobile device’s front camera. To achieve this, we will use combination of few detection methods including: face, eye, pupil, corner detection and calibration of the data.25 pagesenBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Android deviceEye trackingThesis