Name
Abstract | ||
|---|---|---|
In robotic applications of visual simultaneous localization and mapping techniques, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it possible to detect when an image comes from an already perceived scene using local shape and color information. Our approach extends the bag-of-words method used in image classification to incremental conditions and relies on Bayesian filtering to estimate loop-closure probability. We demonstrate the efficiency of our solution by real-time loop-closure detection under strong perceptual aliasing conditions in both indoor and outdoor image sequences taken with a handheld camera. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TRO.2008.2004514 | IEEE Transactions on Robotics |
Keywords | Field | DocType |
Cameras,Simultaneous localization and mapping,Robot vision systems,Current measurement,Layout,Shape,Image classification,Bayesian methods,Filtering,Image sequences | Computer vision,Image sensor,Image processing,Filter (signal processing),Aliasing,Artificial intelligence,Contextual image classification,Simultaneous localization and mapping,Mathematics,Visual Word,Color image | Journal |
Volume | Issue | ISSN |
24 | 5 | 1552-3098 |
Citations | PageRank | References |
172 | 5.80 | 25 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrien Angeli | 1 | 291 | 11.87 |
| David Filliat | 2 | 646 | 47.26 |
| Stéphane Doncieux | 3 | 751 | 39.71 |
| Jean-Arcady Meyer | 4 | 870 | 102.62 |