Toward Object-based Place Recognition in Dense RGB-D Maps

TitleToward Object-based Place Recognition in Dense RGB-D Maps
Publication TypeConference Proceedings
Year of Conference2015
AuthorsFinman R, Paull L, Leonard JJ
Conference NameICRA workshop on visual place recognition in changing environments
Date Published05/2015
Abstract

Longterm localization and mapping requires the
ability to detect when places are being revisited to “close
loops” and mitigate odometry drift. The appearance-based
approaches solve this problem by using visual descriptors to
associate camera imagery. This method has proven remarkably
successful, yet performance will always degrade with drastic
changes in viewpoint or illumination. In this paper, we propose
to leverage the recent results in dense RGB-D mapping to
perform place recognition in the space of objects. We detect
objects from the dense 3-D data using a novel feature descriptor
generated using primitive kernels. These objects are then
connected in a sparse graph which can be quickly searched for
place matches. The developed algorithm allows for multi-floor
or multi-session building-scale dense mapping and is invariant
to viewpoint and illumination. We validate the approach on
a number of real datasets collected with a handheld RGB-D
camera.

PDF: