Name
Abstract | ||
|---|---|---|
Illusions are fascinating and immediately catch peopleu0027s attention and interest, but they are also valuable in terms of giving us insights into human cognition and perception. A good theory of human perception should be able to explain the illusion, and a correct theory will actually give quantifiable results. We investigate here the efficiency of a computational filtering model utilised for modelling the lateral inhibition of retinal ganglion cells and their responses to a range of Geometric Illusions using isotropic Differences of Gaussian filters. This study explores the way in which illusions have been explained and shows how a simple standard model of vision based on classical receptive fields can predict the existence of these illusions as well as the degree of effect. A fundamental contribution of this work is to link bottom-up processes to higher level perception and cognition consistent with Marru0027s theory of vision and edge map representation. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Computer Vision and Pattern Recognition | Journal |
Volume | Citations | PageRank |
abs/1902.02922 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nasim Nematzadeh | 1 | 3 | 1.83 |
| David M. W. Powers | 2 | 500 | 67.39 |
| Trent W. Lewis | 3 | 98 | 10.94 |