Omnidirectional vision and conformal geometric algebra for visual landmark identification

Abstract

SUMMARYThe automatic landmark identification is very important in autonomous robot navigation tasks. In this paper, we use a monocular omnidirectional vision system to extract the image features and the conformal geometric algebra to compute the projective invariants from such features. We show how these features can be used to compute projective and permutationp2-invariantsfrom any kind of omnidirectional vision system. Thep2-invariantsrepresent scene sublandmarks, and a set of them characterize a landmark. The advantage of this representation is that the landmarks are more robust than the single cross-ratio.