Abstract: A method for matching points between three images of a scene comprises retrieving three images acquired by a sensor, extracting blobs from said reflection in said two images; for each given extracted blob of the first image: selecting a selected epipolar plane; identifying plausible combinations; calculating a matching error; repeating the steps of selecting, identifying and calculating for each epipolar plane of the set of epipolar planes; determining a most probable combination; identifying matching points between the two images; validating the matching points between the two images, said validating comprising for each pair of matching points, determining a projection of the pair of matching points in a third image of the third camera; and providing the validated pairs of matching points.

Abstract: A method for matching points between three images of a scene comprises retrieving three images acquired by a sensor, extracting blobs from said reflection in said two images; for each given extracted blob of the first image: selecting a selected epipolar plane; identifying plausible combinations; calculating a matching error; repeating the steps of selecting, identifying and calculating for each epipolar plane of the set of epipolar planes; determining a most probable combination; identifying matching points between the two images; validating the matching points between the two images, said validating comprising for each pair of matching points, determining a projection of the pair of matching points in a third image of the third camera, determining if the projection of the pair of matching points in the third image of the third camera is located on a blob, identifying the pair of matching points as validated if the projection of the pair of matching points in the third image of the third camera is located on

Abstract: A method for matching points between two images of a scene acquired by two cameras, the method including: extracting blobs from the reflection in the images and individually labelling the blobs with a unique identifier; selecting a selected epipolar plane and defining a conjugate epipolar line on each of the images; identifying plausible combinations including a light sheet label of the projected pattern and the unique identifier for a plausible blob selected from the blobs in each of the images; calculating a matching error for each of the plausible combinations; repeating the steps of selecting, identifying and calculating for at least some epipolar planes; determining a most probable combination by computing a figure of merit for the plausible combinations; identifying matching points in the frame from the most probable combination.

Abstract: A method for matching points between two images of a scene acquired by two cameras, the method including: extracting blobs from the reflection in the images and individually labelling the blobs with a unique identifier; selecting a selected epipolar plane and defining a conjugate epipolar line on each of the images; identifying plausible combinations including a light sheet label of the projected pattern and the unique identifier for a plausible blob selected from the blobs in each of the images; calculating a matching error for each of the plausible combinations; repeating the steps of selecting, identifying and calculating for at least some epipolar planes; determining a most probable combination by computing a figure of merit for the plausible combinations; identifying matching points in the frame from the most probable combination.

Abstract: A method for obtaining a refined pose for a 3D sensor for online 3D modeling of a surface geometry of an object, the pose encompassing six degrees of freedom (DOF) including three translation parameters and three orientation parameters, the method comprising: providing the 3D sensor, the 3D sensor being adapted to capture 3D point measurements of the surface of the object from a viewpoint; providing a geometry model of at least part of the surface; observing a portion of the surface of the object with the 3D sensor; measuring an initialization pose for the 3D sensor by at least one of positioning device pose measurement, predicted pose tracking and target observation; finding a best fit arrangement of the 3D point measurements in the geometry model using the initialization pose; generating the refined pose for the 3D sensor using the best fit arrangement.

Abstract: A method for obtaining a refined pose for a 3D sensor for online 3D modeling of a surface geometry of an object, the pose encompassing six degrees of freedom (DOF) including three translation parameters and three orientation parameters, the method comprising: providing the 3D sensor, the 3D sensor being adapted to capture 3D point measurements of the surface of the object from a viewpoint; providing a geometry model of at least part of the surface; observing a portion of the surface of the object with the 3D sensor; measuring an initialization pose for the 3D sensor by at least one of positioning device pose measurement, predicted pose tracking and target observation; finding a best fit arrangement of the 3D point measurements in the geometry model using the initialization pose; generating the refined pose for the 3D sensor using the best fit arrangement.