Name
Abstract | ||
|---|---|---|
The road recognition problem has been solved robustly only for small, often simplified subsets of possible road configurations. A massive augmentation of the amount of used prior knowledge could pave the way towards generally valid estimators. An explicit representation of such knowledge will additionally lead to an efficient, understandable and therefore extendible system. We present a conceptual and a geometrical knowledge representation for the Roads&Junctions domain of discourse. Its parameters are estimated using a multi hypotheses approach. A commercially available digital map and a set of video based object detectors serve as input data. The resulting hypotheses are verified by evaluating the preferred orientations of local texture around the expected position of the lane dividers. The estimate of the camera coordinate system's pose, which is used for image projection, is updated simultaneously. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1524/itit.2007.49.1.5 | IT-INFORMATION TECHNOLOGY |
Keywords | DocType | Volume |
I.2.9 [Robotics] Autonomous Vehicles, I.2.10 [Vision and Scene Understanding] Inner-city Junctions, I.2.4 [Knowledge Representation Formalisms and Methods] Conceptual and Geometrical Modelling, I.2.10 [Vision and Scene Understanding] Estimation Architecture | Journal | 49 |
Issue | ISSN | Citations |
1 | 1611-2776 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Britta Hummel | 1 | 12 | 2.74 |
| Zongru Yang | 2 | 0 | 0.68 |
| Christian Duchow | 3 | 11 | 3.33 |