Abstract: This method of calibration comprising the reconstruction of a 3D mapping of 3D landmarks of an environment on the basis of digital images of the environment captured by the computer-based vision system (10) during the movement of the craft (2) along a trajectory. It comprises the optimization of at least one 3D mapping corresponding to a first sequence of images by considering at least one extrinsic parameter and/or at least one intrinsic parameter and/or at least one parameter of poses and/or one parameter of 3D landmarks as constant and the optimization of at least one 3D mapping corresponding to a second sequence of images, longer than the first image sequence and including the first image sequence, by considering said at least one extrinsic parameter and/or said at least one intrinsic parameter and/or said at least one parameter of poses and/or said at least one parameter of 3D landmarks as variable so as to estimate it.

Abstract: A method for geo-localizing a carrier, comprises: acquiring a plurality of shots of the environment of the carrier; determining at least one datum relating to the position of the carrier for a set of shots; generating a virtual reconstruction of the environment from the shots of the set, from the positional data and from a measurement bias parameter for each position, the virtual reconstruction being parameterized depending on the measurement bias; and modifying the measurement bias parameter to be applied at each position to obtain a virtual reconstruction parameterized by a modified measurement bias, the modification being carried out so as to minimize the distance between the modified virtual reconstruction and an a priori virtual representation of the environment.

Abstract: A method for locating a camera and 3D reconstruction of its static environment, comprising an object of interest, the 3D model of which is known, includes: calculating an initial pose of the camera in the environment and an initial reconstruction; calculating the pose of the camera for each new image by pairing 3D primitives of the environment with 2D primitives of said image and reconstructing 3D primitives of the environment by triangulation; and simultaneously optimizing the poses of the camera and 3D primitives by minimizing a reprojection error over a plurality of images. The 3D model is a geometric description of the object of interest, the reprojection error has only two types of terms, a first type associated with primitives constrained by the 3D model and a second type associated with primitives of the environment other than the object, the optimization associating the primitives with the environment or 3D model.

Abstract: This method of calibration comprising the reconstruction of a 3D mapping of 3D landmarks of an environment on the basis of digital images of the environment captured by the computer-based vision system (10) during the movement of the craft (2) along a trajectory. It comprises the optimization of at least one 3D mapping corresponding to a first sequence of images by considering at least one extrinsic parameter and/or at least one intrinsic parameter and/or at least one parameter of poses and/or one parameter of 3D landmarks as constant and the optimization of at least one 3D mapping corresponding to a second sequence of images, longer than the first image sequence and including the first image sequence, by considering said at least one extrinsic parameter and/or said at least one intrinsic parameter and/or said at least one parameter of poses and/or said at least one parameter of 3D landmarks as variable so as to estimate it.

Abstract: A method for locating a camera and 3D reconstruction of its static environment, comprising an object of interest, the 3D model of which is known, includes: calculating an initial pose of the camera in the environment and an initial reconstruction; calculating the pose of the camera for each new image by pairing 3D primitives of the environment with 2D primitives of said image and reconstructing 3D primitives of the environment by triangulation; and simultaneously optimizing the poses of the camera and 3D primitives by minimizing a reprojection error over a plurality of images. The 3D model is a geometric description of the object of interest, the reprojection error has only two types of terms, a first type associated with primitives constrained by the 3D model and a second type associated with primitives of the environment other than the object, the optimization associating the primitives with the environment or 3D model.

Abstract: An optical installation for determining the relative positions of at least two objects, such as vehicle wheels, includes two optical systems for determining the position of an object in space, each with respect to its observation frame. An optical reference system includes a target visible from the other optical system in the absence of the objects. The other optical system includes a device for analyzing an image of the target and a device for positioning the target with respect to its observation frame, so as to deduce therefrom the position of the observation frame of the other optical system with respect to the observation frame of the of the optical reference system, on the basis of the positions of the target with respect to the observation frame and of the target with respect to the observation frame of the optical reference system.