Title
Enhancing 6D visual relocalisation with depth cameras
Abstract
Relocalisation in 6D is relevant to a variety of Robotics applications and in particular to agile cameras exploring a 3D environment. While the use of geometry has commonly helped to validate appearance as a back-end process in several relocalisation systems before, we are interested in using 3D information to assist fast pose relocalisation computation as part of a front-end task. Our approach rapidly searches for a reduced number of visual descriptors, previously observed and stored in a database, that can be used to effectively compute the camera pose corresponding to the current view. We guide the search by means of constructing validated candidate sets using a 3D test involving the depth information obtained with an RGB-D camera (e.g. stereo of with structured light). Our experiments demonstrate that this process returns a compact quality set that works better for the pose estimation stage than when using a typical Nearest-Neighbor search over appearance only. The improvements are observed in terms of percentage of relocalised frames and speed, where the latter goes up to two orders of magnitude w.r.t. the conventional search.
Year
DOI
Venue
2013
10.1109/IROS.2013.6696457
Intelligent Robots and Systems
Keywords
Field
DocType
SLAM (robots),cameras,computational geometry,data visualisation,pose estimation,robot vision,search problems,stereo image processing,3D environment,3D information,3D test,6D visual relocalisation enhancement,RGB-D camera,agile cameras,backend process,camera pose estimation,compact quality set,depth camera,frame relocalisation,frontend task,geometry,nearest-neighbor search,pose relocalisation computation,robotics applications,visual descriptor
Computer vision,Data visualization,Structured light,Computer science,Computational geometry,Agile software development,Pose,Artificial intelligence,RGB color model,Robotics,Computation
Conference
ISSN
Citations 
PageRank 
2153-0858
6
0.42
References 
Authors
0
5