Abstract
In this paper, we study 3D object reconstruction based on a set of 2D images. In order to get the best camera path that increases accuracy we focus on this strategy to be used. Euclidean 3D image-based reconstruction is developed in three steps, which are primitive extraction, correspondence of these primitives and then triangulation. The extraction and triangulation are purely geometrical, whereas the matching step can have precision issues especially in the case of noisy images. An experimental study is carried out where a camera is attached to a robot arm and moved precisely relative to a scene containing a checkerboard calibration pattern. The reconstruction results are compared with values of motion given to the robot. A geometric and analytical study of the impact of the motion of the camera with respect to the scene on the error of a 3D image-based reconstructed point was also carried out. It has been demonstrated that the impact of a correspondence error on the reconstruction accuracy point varies drastically depending on the image capture strategy.
Configuration-based compliance control of kinematically redundant robot arm Part I: Theoretical framework
