Name
Abstract | ||
|---|---|---|
Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s10851-012-0384-5 | Journal of Mathematical Imaging and Vision |
Keywords | DocType | Volume |
Space-variant representation,Log-polar mapping,Onboard vision applications | Journal | 47 |
Issue | ISSN | Citations |
1-2 | 0924-9907 | 1 |
PageRank | References | Authors |
0.36 | 31 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naveen Onkarappa | 1 | 21 | 4.11 |
| Angel Domingo Sappa | 2 | 565 | 33.54 |