DOI: https://doi.org/10.15368/theses.2020.162
Available at: https://digitalcommons.calpoly.edu/theses/2250
Date of Award
12-2020
Degree Name
MS in Computer Science
Department/Program
Computer Science
College
College of Engineering
Advisor
Christian Eckhardt
Advisor Department
Computer Science
Advisor College
College of Engineering
Abstract
Projection mapping, a subtopic of augmented reality, displays computer-generated light visualizations from projectors onto the real environment. A challenge for projection mapping in performing interactive arts is dynamic body movements. Accuracy and speed are key components for an immersive application of body projection mapping and dependent on scanning and processing time.
This thesis presents a novel technique to achieve real-time body projection mapping utilizing a state of the art body tracking device, Microsoft’s Azure Kinect DK, by using an array of trackers for error minimization and movement prediction. The device's Sensor and Bodytracking SDKs allow multiple device synchronization. We combine our tracking results from this feature with motion prediction to provide an accurate approximation for body joint tracking. Using the new joint approximations and the depth information from the Kinect, we create a silhouette and map textures and animations to it before projecting it back onto the user. Our implementation of gesture detection provides interaction between the user and the projected images.
Our results decreased the lag time created from the devices, code, and projector to create a realistic real-time body projection mapping. Our end goal was to display it in an art show. This thesis was presented at Burning Man 2019 and Delfines de San Carlos 2020 as interactive art installations.