BMVC 2004, Kingston, 7th-9th Sept, 2004

Central Catadioptric Line Detection
P. Vasseur and E. M. Mouaddib (UPJV, France)

Central catadioptric sensors enable to acquire panoramic images on a 360
degree field of view while preserving a single viewpoint. These advantages
account for the growing use of these sensors in applications such as surveillance,
navigation or modelling. However, the deformations of the image do
not allow to apply classical perspective image algorithms or operators. Typically,
straight line detection in perspective image becomes a delicate and
complex conic detection problem in central catadioptric image. Previous
methods proposed in the literature were essentially motivated by particular
cases such as horizontal line detection or paracatadioptric line detection. In
this paper, we propose an algorithm which consists in performing the detection
in the space of the equivalent sphere which is the unified domain of
central catadioptric sensors. On this sphere, real lines are projected into great
circles that we detect thanks to the Hough transform. We also propose to
apply this unifying model in order to perform the calibration of the intrinsic
parameters required for the projection on the sphere. We show results on
synthetic and real catadioptric images (parabolic, hyperbolic) to demonstrate
the relevance of the detection on the sphere.
(pdf article)