RGBD relocalisation using pairwise geometry and concise key point sets

Shuda Li; Andrew Calway

ICRA 2015poster26 citations

RGBD relocalisation using pairwise geometry and concise key point sets

Abstract

We describe a novel RGBD relocalisation algorithm based on key point matching. It combines two components. 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.

BibTeX

@inproceedings{icra2015_rgbdrelocalisati,
  title = {RGBD relocalisation using pairwise geometry and concise key point sets},
  author = {Shuda Li and Andrew Calway},
  booktitle = {ICRA 2015},
  year = {2015}
}