Previous works have shown that catadioptric systems are particularly suited for
egomotion estimation thanks to their large field of view and thus numerous al-
gorithms have already been proposed in the literature to estimate the motion. In
this paper, we present a method for estimating six degrees of freedom camera mo-
tions from central catadioptric images in man-made environments. State-of-the-art
methods can obtain very impressive results. However our proposed system provides
two strong advantages over the existing methods: first, it can implicitly handle the
difficulty of planar/non-planar scenes, and second, it is computationally much less
expensive. The only assumption deals with the presence of parallel straight lines
which is reasonable in a man-made environment. More precisely, we estimate the
motion by decoupling the rotation and the translation. The rotation is computed
by an e±cient algorithm based on the detection of dominant bundles of parallel
catadioptric lines and the translation is calculated from a robust 2-point algorithm.
We also show that the line-based approach allows to estimate the absolute attitude
(roll and pitch angles) at each frame, without error accumulation. The efficiency
of our approach has been validated by experiments in both indoor and outdoor
environments and also by comparison with other existing methods.