Master’s Thesis: Comprehensive Facial Data and Gaze Extraction Using iPhone Front Camera and ARKit

23.03.2026, Diplomarbeiten, Bachelor- und Masterarbeiten

Face and eye-gaze tracking technologies have advanced significantly with the rise of augmented reality (AR) and computer vision applications. The iPhone's TrueDepth camera, combined with Apple’s ARKit, provides a powerful tool for capturing detailed facial data and gaze information in real time.

This research aims to explore the full potential of the iPhone front camera and ARKit for extracting various facial attributes, including:

Face orientation (head pose tracking)
Gaze estimation (eye-tracking and attention focus)

By leveraging ARKit's advanced face-tracking capabilities, our goal is to collect, analyze, and evaluate facial data under various conditions, exploring its potential applications in human-computer interaction (HCI) and accessibility solutions.

Your goal is to extract the facial features and robustly estimate the gaze direction and head orientation in a real-world scenario. The solutions should be evaluated using ground truth data from external eye-tracking devices or computer vision models.

Prerequisites:

Experience with OpenCV, Python, and Swift.
Knowledge of ARKit would be beneficial.
Self-motivated and independent approach to work.

Kontakt: tim.schreiter@tum.de

More Information

https://www.ce.cit.tum.de/pins/open-positions/student-positions/