Name
Abstract | ||
|---|---|---|
Systems for automated image analysis are useful for a variety of tasks. Their importance is still growing due to technological advances and increased social acceptance. Especially driver assistance systems have reached a high level of sophistication. Fully or partly autonomously guided vehicles, particularly for road traffic, require highly reliable algorithms due to the conditions imposed by natural environments. At the Institut für Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a system extracting important information from an image taken by a CCD camera installed at the rear-view mirror in a car. The approach is divided into a sequential and a parallel phase of sensor and information processing. Three main tasks, namely initial segmentation (object detection), object tracking and object classification are realized by integration in the sequential phase and by fusion in the parallel phase. The main advantage of this approach is integrative coupling of different algorithms providing partly redundant information. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0262-8856(99)00032-3 | Image and Vision Computing |
Keywords | DocType | Volume |
Driver assistance,Machine vision,Data fusion | Journal | 18 |
Issue | ISSN | Citations |
5 | 0262-8856 | 73 |
PageRank | References | Authors |
12.88 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Uwe Handmann | 1 | 139 | 27.63 |
| thomas kalinke | 2 | 134 | 26.81 |
| christos tzomakas | 3 | 123 | 23.55 |
| M Werner | 4 | 73 | 12.88 |
| W von Seelen | 5 | 503 | 140.13 |