An on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry is presented. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework for integration of the two data-sources into a coherent framework through uncertainty based fusion/arbitration.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54970 |
| Date | 27 May 2016 |
| Creators | Singhal, Prateek |
| Contributors | Christensen, Henrik |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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