You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Gesture Recognition Using Evolution Strategy Neural Network

Fulltext:


Research group:


Publication Type:

Conference/Workshop Paper

Venue:

ETFA 2008

Publisher:

IEEE


Abstract

A new approach to interact with an industrial robot using hand gestures is presented. System proposed here can learn first time user’s hand gestures rapidly. This improves product usability and acceptability. Artificial neural networks trained with the evolution strategy technique are found to be suited for this problem. The gesture recognition system is an integrated part of a larger project for addressing intelligent human-robot interaction using a novel multi-modal paradigm. The goal of the overall project is to address complexity issues related to robot programming by providing a multi-modal user friendly interacting system that can be used by SMEs.

Bibtex

@inproceedings{Hagg1370,
author = {Johan H{\"a}gg and Batu Akan and Baran {\c{C}}{\"u}r{\"u}kl{\"u} and Lars Asplund},
title = {Gesture Recognition Using Evolution Strategy Neural Network},
editor = {.},
pages = {245--248},
month = {September},
year = {2008},
booktitle = {ETFA 2008},
publisher = {IEEE},
url = {http://www.es.mdu.se/publications/1370-}
}