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This paper presents a new coded structured light pattern which permits to solve the correspondence problem by a single shot and without using geometrical constraints. The pattern is composed by the projection of a grid made by coloured slits in such a way that each slit with its two neighbours appears only once in the pattern. The technique proposed permits a rapid and robust 3D scene measurement, even with moving objects. Ó

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International audience2D visual servoing consists in using data provided by a vision sensor for controlling the motions of a dynamic system. Most of visual servoing approaches has relied on the geometric features that have to be tracked and matched in the image acquired by the camera. Recent works have highlighted the interest of taking into account the photometric information of the entire image. This approach was tackled with images of perspective cameras. We propose, in this paper, to extend this technique to central cameras. This generalization allows to apply this kind of method to catadioptric cameras and wide field of view cameras. Several experiments have been successfully done with a fisheye camera in order to control a 6 degrees of freedom (dof) robot and with a catadioptric camera for a mobile robot navigation task

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.

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