| dc.contributor.author | Segers, Vaughn | |
| dc.contributor.author | Connan, James | |
| dc.date.accessioned | 2009-11-19T12:23:16Z | |
| dc.date.available | 2009-11-19T12:23:16Z | |
| dc.date.issued | 2009 | |
| dc.identifier.citation | Segers, V. & Connan, J. (2009) Real-time gesture recognition using eigenvectors. Proc. Southern Africa Telecommunication Networks and Applications Conference (SATNAC 2009), Royal Swazi Spa, Ezulwini, Swaziland, 363-366 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10566/63 | |
| dc.description.abstract | This paper discusses an implementation for gesture
recognition using eigenvectors under controlled conditions. This
application of eigenvector recognition is trained on a set of
defined hand images. Training images are processed using eigen
techniques from the OpenCV image processing library. Test images are then compared in real-time. These techniques are
outlined below. | en_US |
| dc.description.sponsorship | Telkom. CISCO, THRIP | en_US |
| dc.language.iso | en | en_US |
| dc.rights | This file may be freely used for educational purposes, as long as it is not altered in any way. Acknowledgement of the authors and the source is required | |
| dc.subject | Hand shape | en_US |
| dc.subject | Gesture recognition | en_US |
| dc.subject | Eigenvectors | en_US |
| dc.subject | Sign language | en_US |
| dc.title | Real-time gesture recognition using eigenvectors | en_US |
| dc.type | Conference Paper | en_US |
| dc.inquiries | jconnan@uwc.ac.za | |
