Natural hand gestures for human identification in a Human-Computer Interface
Abstract
The goal of this work is the identification of humans based on motion data in the form of natural hand gestures. In this paper, the identification problem is formulated as classification with classes corresponding to persons' identities, based on recorded signals of performed gestures. The identification performance is examined with a database of twenty-two natural hand gestures recorded with two types of hardware and three state-of-art classifiers: Linear Discrimination Analysis (LDA), Support Vector machines (SVM) and k-Nearest Neighbour (k-NN). Results show that natural hand gestures allow for an effective human classification.
Keywords
Cite
@article{arxiv.1109.5034,
title = {Natural hand gestures for human identification in a Human-Computer Interface},
author = {Michał Romaszewski and Przemysław Głomb and Piotr Gawron},
journal= {arXiv preprint arXiv:1109.5034},
year = {2013}
}
Comments
13 pages, 3 figures, This is a major rewrite of previous version of the paper. The same dataset as in previous version was used. The analysis is now focused on application of the gestures classification methods to human identification