%0 Journal Article 
%F LEMAIRE-IJCV-2007
%A Lemaire, T.
%A Berger, Cyrille
%A Jung, I-K.
%A Lacroix, S.
%T Vision-based {SLAM}: stereo and monocular approaches
%J International Journal on Computer Vision
%V 74
%N 3
%P 343-364
%X Building a spatially consistent model is a key functionality to endow a mobile robot with autonomy. Without an initial map or an absolute localization means, it requires to concurrently solve the localization and mapping problems. For this purpose, vision is a powerful sensor, because it provides data from which stable features can be extracted and matched as the robot moves. But it does not directly provide 3D information, which is a difficulty for estimating the geometry of the environment. This article presents two approaches to the SLAM problem using vision: one with stereovision, and one with monocular images. Both approaches rely on a robust interest point matching algorithm that works in very diverse environments. The stereovision based approach is a classic SLAM implementation, whereas the monocular approach introduces a new way to initialize landmarks. Both approaches are analyzed and compared with extensive experimental results, with a rover and a blimp
%U http://homepages.laas.fr/simon/publis/LEMAIRE-IJCV-2007.pdf
%8 
%D 2007
%K  slam