We describe a novel RGBD relocalisation algorithm based on key point matching. It combines two com- ponents. First, a graph matching algorithm which takes into account the pairwise 3-D geometry amongst the key points, giving robust relocalisation. Second, a point selection process which provides an even distribution of the ‘most matchable’ points across the scene based on non-maximum suppression within voxels of a volumetric grid. This ensures a bounded set of matchable key points which enables tractable and scalable graph matching at frame rate. We present evaluations using a public dataset and our own more difficult dataset containing large pose changes, fast motion and non-stationary objects. It is shown that the method significantly out performs state-of-the-art methods.
|Name||Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) |
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Conference||2015 IEEE International Conference on Robotics and Automation|
|Period||26/05/15 → 30/05/15|
- computer vision