Interest Point Detectors for Visual SLAM
Óscar Martínez Mozos, Arturo Gil, Mónica Ballesta, and Oscar Reinoso
Proc. of the Conference of the Spanish Association for Artificial Intelligence (CAEPIA).   (Salamanca, Spain. November 2007.)


In this paper we present several interest points detectors and we analyze their suitability when used as landmark extractors for vision-based simultaneous localization and mapping (vSLAM). For this purpose, we evaluate the detectors according to their repeatability under changes in viewpoint and scale. These are the desired requirements for visual landmarks. Several experiments were carried out using sequence of images captured with high precision. The sequences represent planar objects as well as 3D scenes.