1. Towards Geographical Referencing of Monocular SLAM Reconstruction Using 3D City Models: Application to Real- Time Accurate Vision-Based Localization Reporter : 鄒嘉恆 Date : 2010/05/04 CVPR ‘09

2. Introduction

3. Outline Motivation Coarse SLAM Reconstruction Bundle adjustment Experimental results Application Conclusion

4. Motivation Current SLAM methods are still prone to drift errors, which prevent their use in large-scale applications.

5. Coarse SLAM Reconstruction

7. SLAM(Simultaneous localization and mapping)

8. Coarse SLAM Reconstruction

9. Coarse SLAM Reconstruction- SLAM reconstruction fragmentation Use the idea suggested by Lowe in [11] to segment the trajectory. [11]D. G. Lowe. Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence, 31(3):355–395, 1987. 3D points

10. Coarse SLAM Reconstruction

11. Coarse SLAM Reconstruction- Non-rigid ICP Goal ： Point-plane association : Robust estimation : 3D Model

12. Coarse SLAM Reconstruction Result

13. Bundle adjustment

14. Advantages to use the barycentre of backprojections:  The movement of Q i ’ is then directly linked to the displacement of the cameras.  Q i position is not used in the cost function.

15. Experimental results Synthetic sequence

16. Experimental results Real sequence 640x480, 1500 meters

17. Application

18. Conclusion Proposed a new approach to correct large- scale SLAM reconstructions. Proposed AR application shows that the obtained reconstruction precision is sufficient.