Date of Award

Spring 2025

Degree Type

Thesis

Department

Computer Science and Engineering

Director of Thesis

Dr. Jason D. Bakos

Second Reader

Dr. Steven Lynn

Abstract

In response to the growing demand for smarter, more responsive face tracking cameras in the post-pandemic world, our team designed SWVL, a custom AI-powered face tracking gimbal meant to address the limitations commonly encountered by the commercial models currently on the market. These commercially available gimbals come with several issues, such as frequently losing track of the person in the frame and requiring manual resets, which we sought to fix with our implementation. We designed a system with fully custom hardware and software including a 3D printed dual-axis camera gimbal driven by stepper motors, a control PCB based around an ESP32 microcontroller, and a Python-based face tracking pipeline with a custom model and MobileNetV3-Large backbone. The model communicates with an Electron UI and Python backend that work together to keep the user centered in the frame. Although it has some shortcomings, we largely achieved all our objectives and were able to produce a gimbal that is quite e!ective in tracking the user as they move throughout the environment. All of the code and project files for SWVL can be found on GitHub at https://github.com/alexthecat123/SWVL.

First Page

1

Last Page

29

Rights

© 2025, Alexander J. Anderson-McLeod, Jakub Jerzmanowski, Michael Laitarovsky, Trevor Allison, & Jagger Tanner

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