Evolving Encoded Marking for Glove-Based Pose and Posture Recognition

Joshua V Gyllinsky, University of Rhode Island

Abstract

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.^

Subject Area

Computer engineering|Artificial intelligence|Computer science

Recommended Citation

Joshua V Gyllinsky, "Evolving Encoded Marking for Glove-Based Pose and Posture Recognition" (2018). Dissertations and Master's Theses (Campus Access). Paper AAI10792807.
https://digitalcommons.uri.edu/dissertations/AAI10792807

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