Title: Deep Learning based Eye Tracking and Head Movement Detection
Subject: Computer science,Embedded systems,Robotics
Level: Basic/Advanced
Description: When human communicates with each other through speech, several gestures such as facial expressions, eye movement, head movement etc. provide complementary information as communication channels [1]. Eye tracking and head movement detection are one of the most interesting research area in the field of Image Processing and Computer Vision and the tasks are the fundamental contributor for human computer interaction (HCI).

Eye tracking and head movement detection are co-related with each other and have been an active research field in the past years as it adds convenience to a variety of applications. Both technologies are considered the easiest alternative interface methods. Eye tracking means the process of measuring either the point of gaze (where one is looking) or the motion of an eye relative to the head. For both eye tracking and head movement detection, several different approaches have been proposed and used to implement different algorithms for these technologies. Examples of different fields of applications for both technologies, such as human-computer interaction, driving assistance systems [2], and assistive technologies need to be investigated.

In this project, you need to use image processing and computer vision techniques to build your intelligent system with the help of different artificial intelligence algorithms.

The project works can be subdivided as follows:
1. Literature study and survey of existing methods and systems
2. Data Collection using Camera both lab environment and driving situation
3. Develop expected methods
4. Evaluation
5. Outcome

Successfully eye tracking and head movement detection will be the expected outcome in different angles, positions and situations.

Extra Qualification: Image processing and Computer vision Concept (or highly ambitious to learn)
Start date: 2019-01-21
End date: 2019-06-12
Prerequisites:
IDT supervisors: Mobyen Uddin Ahmed, Hamidur Rahman
Examiner: Shahina Begum
Comments: