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Towards an approach for knowledge-based road detection
| Content Provider | ACM Digital Library |
|---|---|
| Author | Foedisch, Mike Shneier, Michael Schlenoff, Craig |
| Abstract | Our previous work on road detection suggests the usage of prior knowledge in order to improve performance. In this paper we will explain our motivation for a novel approach, define requirements and point out issues, particularly concerning the representation of road depending on the use, which need to be addressed. The proposed system will provide symbolic data for high-level processes and guidance for low-level processes. Furthermore, we will outline the recognition approach based on previously discussed requirements and issues. This paper has a visionary character based on our experience with road detection for autonomous road vehicles. |
| Starting Page | 1 |
| Ending Page | 8 |
| Page Count | 8 |
| File Format | |
| ISBN | 159593202X |
| DOI | 10.1145/1096961.1096962 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2005-11-04 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Model-based recognition Road detection Constraints Road representation Autonomous driving Tree search Road recognition |
| Content Type | Text |
| Resource Type | Article |
