Fusion of Time-of-Flight Plane Features with Point Features for Camera-Pose Tracking

Abstract

The objective of this master thesis is to estimate the pose change of a time of flight (TOF) camera between consecutive frames in all six degrees of freedom. To gain visual highresolution information of the scene, the TOF camera is combined with an RGB camera.
The proposed algorithm fuses 3D geometric and 2D visual features. Planar surfaces are extracted directly from the 3D point cloud while SURF is applied to the 2D projections of these surfaces. Feature positions and plane equations are both used to estimate all six degrees of freedom of the camera motion. The algorithm outperforms fast coarse pose registrations, that do not combine the 3D geometry with visual projections in accuracy while it is suitable for online processing. Fine registrations, that use the complete point cloud are more precise but also much more time consuming.

Contacts

• Student: Sebastian Marsch
• Supervisor: Christian Waechter
• Director: Gudrun Klinker