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

MotivationCoarse SLAM ReconstructionBundle adjustmentExperimental resultsApplicationConclusion

Motivation

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

Coarse SLAM Reconstruction

Coarse SLAM Reconstruction

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, 1987.

3D points

Coarse SLAM Reconstruction

Coarse SLAM Reconstruction-Non-rigid ICP

Goal：

Point-plane association :

Robust estimation :

3D Model

Coarse SLAM Reconstruction

Result

Bundle adjustment

Bundle adjustment

Advantages to use the barycentre of backprojections:The movement of Qi’ is then directly linked to

the displacement of the cameras.Qi position is not used in the cost function.

Experimental results

Synthetic sequence

Experimental results

Real sequence640x480, 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.