Cooperative Gesture Recognition - Learning Characteristics of Classifiers and Navigating the User to an Ideal Situation

Hiromasa Yoshimoto, Yuichi Nakamura

2015

Abstract

This paper introduces a novel scheme of gesture interface that guides the user toward obtaining better performance and usability. The accuracy of gesture recognition is heavily affected by how the user makes postures and moves, as well as environmental conditions such as lighting. The usability of the gesture interface can potentially be improved by notifying the user of when and how better accuracy is obtained. For this purpose, we propose a method for estimating the performance of gesture recognition in its current condition, and a method for suggesting possible ways to improve performance to the user. In performance estimation, accuracy in the current condition is estimated based on supervised learning with a large number of samples and corresponding ground truths. If the estimated accuracy is insufficient, the module searches for better conditions that can be reached with the user’s cooperation. If a good improvement is possible, the way to improve is communicated to the user in terms of visual feedback, which shows how to avoid or how to recover from the undesirable condition. In this way, users benefit, i.e., better accuracy and usability, by cooperating with the gesture interface.

Paper Citation

in Harvard Style

Yoshimoto H. and Nakamura Y. (2015). Cooperative Gesture Recognition - Learning Characteristics of Classifiers and Navigating the User to an Ideal Situation . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-758-077-2, pages 210-218. DOI: 10.5220/0005206902100218

in Bibtex Style

@conference{icpram15,
author={Hiromasa Yoshimoto and Yuichi Nakamura},
title={Cooperative Gesture Recognition - Learning Characteristics of Classifiers and Navigating the User to an Ideal Situation},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2015},
pages={210-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005206902100218},
isbn={978-989-758-077-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - Cooperative Gesture Recognition - Learning Characteristics of Classifiers and Navigating the User to an Ideal Situation
SN - 978-989-758-077-2
AU - Yoshimoto H.
AU - Nakamura Y.
PY - 2015
SP - 210
EP - 218
DO - 10.5220/0005206902100218