Name
Abstract | ||
|---|---|---|
An original approach to the recovery of 3-D shape information from 2-D images is described. The approach is based on an architecture made up by two cascaded neural networks. The first network is an implementation of the Boundary Contour System aimed to extract a brightness gradient map from the image. The second is a backpropagation network that estimates the geometric parameters of the object parts present in the acquired scene. A description of simulations of the implemented architecture and the quite satisfactory experimental results are reported as well as the comparisons with some classic approaches to the problem. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1016/0167-8655(94)90103-1 | Pattern Recognition Letters |
Keywords | Field | DocType |
artificial vision,connectionism,shape from shading,connectionist architecture,shape from shading.,3-d form feature,backpropagation,neural network | Computer vision,Architecture,Pattern recognition,Computer science,Artificial intelligence,Backpropagation,Photometric stereo,Brightness,Artificial vision,Connectionism | Journal |
Volume | Issue | ISSN |
15 | 1 | Pattern Recognition Letters |
Citations | PageRank | References |
1 | 0.41 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| E. Ardizzone | 1 | 158 | 22.06 |
| A. Chella | 2 | 216 | 15.99 |
| R. Pirrone | 3 | 25 | 3.89 |
| F. Sorbello | 4 | 112 | 13.73 |