Cameraman (Zoom Assistant)
Authors: Samson Huang, Nicolas Rodriguez, Elias Munoz, Shamin Mashalkar
Faculty Supervisor: Hao Jiang
Department: Engineering
Zoom has recently revolutionized traditional learning by offering students to attend class remotely. However, since the recent pandemic this option has mostly disappeared, especially, for students in STEM. We propose an easy to use Zoom assistant, a wide-lens webcam which will follow a Professor and frame the webcam video around them. To achieve this we will utilize face detection, body tracking, and Bluetooth tracking. We firstly utilize face detection to frame our x, y, and z-axis around the Professor. The body tracking will mostly be used to change the x-axis if the Professor ever turns his head, making our face detection fail. The Bluetooth tracking will be a wearable remote which will track the Professor. So when multiple faces or bodies are in frame, the Professor stays in frame. The wearable remote will also take in some input allowing the Professor to make a fixed frame, which they will be able to toggle to. This video will be processed from a Nvidia Jetson Nano and streamed to an outside computer.