Volume 12, Number 04, February 2022

An Automated Video Content Customization System using Eye Tracking and Artificial Intelligence

  Authors

Yuyang Lou¹ and Yu Sun², ¹Charles Wright Academy, USA, ²California State Polytechnic University, USA

  Abstract

In the past few years, the internet and online social networks developed drastically, promoting the development of online learning programs. These programs provided opportunities for a digital learning experience that allows students to explore beyond what's taught in school. However, having a clear understanding of what topic might interest the user and motivate the user to further explore that topic is hard for both the user and the learning program. This paper proposes to create one centralized method of predicting what the user would be interested in and provide them with educational content recommendations. Our design builds upon the eyetracking techniques, which allows us to capture users’ eye movements, and object recognition achieved by machine learning, which allows us to examine the specific object that the users are looking at and provide data for the users’ interest analysis [3]. Our results show a success rate of 90% of analyzing what the user is truly looking at. We used our decision heuristic, etc.

  Keywords

Eye Tracking, Deep learning, computer vision.