Name
Abstract | ||
|---|---|---|
We describe a new method for detecting features on a marked RoboCup field. We implemented the framework for robots with omnidirectional vision, but the method can be easily adapted to other systems. The focus is on the recognition of the center circle and four different corners occurring in the penalty area. Our constructive approach differs from previous methods, in that we aim to detect a whole palette of different features, hierarchically ordered and possibly containing each other. High-level features, such as the center circle or the corners, are constructed from low-level features such as arcs and lines. The feature detection process starts with low-level features and iteratively constructs higher features. In RoboCup the method is valuable for robot self-localization; in other fields of application the method is useful for object recognition using shape information. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-32256-6_6 | RobuCup |
Keywords | Field | DocType |
constructive approach,object recognition,robotic vision,constructive feature detection approach,different feature,previous method,center circle,different corner,new method,low-level feature,feature detection process,marked robocup field,feature detection | Computer vision,Omnidirectional vision,Feature detection,Constructive,Feature (computer vision),Computer science,Artificial intelligence,Robot,Monte Carlo localization,Cognitive neuroscience of visual object recognition | Conference |
Volume | ISSN | ISBN |
3276 | 0302-9743 | 3-540-25046-8 |
Citations | PageRank | References |
1 | 0.39 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Felix Von Hundelshausen | 1 | 169 | 15.13 |
| Michael Schreiber | 2 | 258 | 25.42 |
| Raúl Rojas | 3 | 189 | 22.57 |