Name
Abstract | ||
|---|---|---|
Radial Basis Function (RBF) networks are compared with other neural network techniques on a face recognition task for applications involving identification of individuals using low resolution video information. The RBF networks have been shown to exhibit useful shift, scale and pose (y-axis rotation) invariance after training, when the input representation is made to mimic the receptive field functions found in early stages of the human vision system. Extensions of the techniques to the case of image sequence analysis are described and a Time Delay (TD) RBF network is used for recognising simple movement-based gestures. Finally, we discuss how these techniques can be used in real-life applications that require recognition of faces and gestures using low resolution video images. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/3-540-63930-6_163 | ACCV (1) |
Keywords | DocType | ISBN |
neural networks,learning identity,neural network,radial basis function,low resolution,receptive field,face recognition | Conference | 3-540-63930-6 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| jon howell | 1 | 585 | 39.63 |
| Hilary Buxton | 2 | 491 | 135.93 |