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

Introduction

Outline Motivation Coarse SLAM Reconstruction Bundle adjustment Experimental results Application Conclusion

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

Coarse SLAM Reconstruction

SLAM(Simultaneous localization and mapping)

Coarse SLAM Reconstruction

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, D points

Coarse SLAM Reconstruction

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

Coarse SLAM Reconstruction Result

Bundle adjustment

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.

Experimental results Synthetic sequence

Experimental results Real sequence 640x480, 1500 meters

Application

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