AN APPLICATION OF GRAPH DIFFUSION FOR GESTURE CLASSIFICATION

Loading...
Thumbnail Image

Date

2020

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

294
views
231
downloads

Abstract

Reliable and widely available robotic prostheses have long been a dream of science fiction writers and researchers alike. The problem of sufficiently generalizable gesture recognition algorithms and technology remains a barrier to these ambitions despite numerous advances in computer science, engineering, and machine learning. Often the failure of a particular algorithm to generalize to the population at large is due to superficial characteristics of subjects in the training data set. These superficial characteristics are captured and integrated into the signal intended to capture the gesture being performed. This work applies methods developed in computer vision

and graph theory to the problem of identifying pertinent features in a set of time series modalities.

Description

Provenance

Citation

Citation

Voisin, Perry Samuel (2020). AN APPLICATION OF GRAPH DIFFUSION FOR GESTURE CLASSIFICATION. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/20804.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.