Date of Award
Master of Science in Computer Science
Computer Science and Statistics
The feasibility of encoding pose and posture information within surface textures for digital reconstruction of the inverse-mapping problem of computer vision was explored. This was done using a combination of three biology-inspired artificial intelligence techniques. Initial steps were conducted in this pursuit and the path to further research is laid out. It was found that textures can be used to encode information on a 3D surface to supplement computer vision systems.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Gyllinsky, Joshua V., "Evolving Encoded Marking for Glove-Based Pose and Posture Recognition" (2018). Open Access Master's Theses. Paper 1246.
Available for download on Monday, April 20, 2020