Abstract:
In this paper we propose an automatic visual based technique, integrated in a wayside monitoring system for train inspection, that allows to assess the attitude of the me...Show MoreMetadata
Abstract:
In this paper we propose an automatic visual based technique, integrated in a wayside monitoring system for train inspection, that allows to assess the attitude of the metal bow of a pantograph by combining a colour image captured by an RGB digital camera and a pointcloud built from a range sensor scan. An efficient and fast template-matching procedure allows to detect the pantograph in the scene and associate a matching attitude, searching for the most similar model present in a database. The record of templates belonging to the database exploits a virtual rendering environment that allows to optimize the training stage in terms of computational load and time. During actual inspection the RGB image and pointcloud of the pantograph are opportunely processed and aligned to the same reference frame. After the preliminary template-matching step, the pointcloud is augmented with the virtual model of the matched template and the attitude angular values are refined by applying the iterative closest point (ICP) algorithm between the real object and the virtual one, with the aim of reducing eventual residual errors.
Published in: 2016 IEEE International Smart Cities Conference (ISC2)
Date of Conference: 12-15 September 2016
Date Added to IEEE Xplore: 03 October 2016
ISBN Information: