Name
Abstract | ||
|---|---|---|
The Self-Organising Artificial Neural Network Models, of which we have used the Growing Neural Gas (GNG) can be applied to preserve the topology of an input distribution. Traditionally these models neither do include local adaptation of the nodes nor colour information. In this paper, we extend GNG by presenting an improvement to the network that has both global and local properties and can track in cluttered backgrounds. The method performs continuously mapping over a distribution that changes over time and works with both smooth and abrupt changes. The central mechanism relies on the addition of global and local attributes, and skin colour information to the network which allow us to automatically model and track 2D gestures. Application to hand gesture video tracking is presented. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IJCNN.2010.5596288 | 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 |
Keywords | Field | DocType |
skin,gesture recognition,topology,shape,artificial neural network,network topology,computational modeling,video tracking | Computer vision,Pattern recognition,Gesture,Computer science,Gesture recognition,Network topology,Video tracking,Artificial intelligence,Artificial neural network,Self organisation,Machine learning,Neural gas | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anastassia Angelopoulou | 1 | 102 | 21.29 |
| José García Rodríguez | 2 | 192 | 29.10 |
| Alexandra Psarrou | 3 | 199 | 27.14 |
| Gaurav Gupta | 4 | 14 | 7.06 |