Name
Abstract | ||
|---|---|---|
The use of omni-directional cameras has become increasingly popular in vision systems for video surveillance and autonomous robot navigation. However, to date most of the research relating to omni-directional cameras has focussed on the design of the camera or the way in which to project the omni-directional image to a panoramic view rather than the processing of such images after capture. Typically images obtained from omni-directional cameras are transformed to sparse panoramic images that are interpolated to obtain a complete panoramic view prior to low level image processing. This interpolation presents a significant computational overhead with respect to real-time vision.We present an efficient design procedure for space variant feature extraction operators that can be applied to a sparse panoramic image and directly processes this sparse image. This paper highlights the reduction of the computational overheads of directly processing images arising from omni-directional cameras through efficient coding and storage, whilst retaining accuracy sufficient for application to real-time robot vision. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s10851-008-0107-0 | Journal of Mathematical Imaging and Vision |
Keywords | Field | DocType |
Sparse images,Space variant operators,Omni-directional images | Overhead (computing),Computer vision,Robot vision,Computer graphics (images),Computer science,Interpolation,Image processing,Coding (social sciences),Feature extraction,Sparse image,Operator (computer programming),Artificial intelligence | Journal |
Volume | Issue | ISSN |
32 | 3 | 0924-9907 |
Citations | PageRank | References |
0 | 0.34 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sonya Coleman | 1 | 216 | 36.84 |
| Bryan W. Scotney | 2 | 670 | 82.50 |
| Dermot Kerr | 3 | 50 | 13.84 |