author = {Tom Botterill and Steven Mills and Richard Green},
title = {Correcting Scale Drift by Object Recognition in Single Camera SLAM},
journal = {To appear in IEEE Transactions on Systems, Man, and Cybernetics--Part B: Cybernetics},
year = {2012},
volume = {-},
abstract={This paper proposes a novel solution to the problem
of scale drift in single camera SLAM, based on recognising
and measuring objects. When reconstructing the trajectory of
a camera moving in an unknown environment, the scale of
the environment, and equivalently the speed of the camera, is
obtained by accumulating relative scale estimates over sequences
of frames. This leads to scale drift: errors in scale accumulate
over time. The proposed solution is to learn the classes of
objects which appear throughout the environment, then to use
measurements of the size of these objects to improve the scale
estimate. A Bag-of-Words-based scheme to learn object classes,
to recognise object instances, and to use these observations to
correct scale drift is described, and is demonstrated reducing
accumulated errors by 64% while navigating for 2.5km through
a dynamic outdoor environment.},