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A novel method for displacement monitoring by using RGB+D data has been recently proposed. RGB+D data is created by fusing image and laser scan data, where the D channel represents the distance, interpolated from laser scanner data. RGB+D image combines the advantages of the two measuring methods. Laser scans for distance changes in the line of sight and high-resolution image data for displacements perpendicular to the viewing direction of the camera. Image feature detection and matching algorithms detect and match discrete points within RGB+D images from different epochs. 3D coordinates of the points can be easily calculated from RGB+D images. In this paper, implementation of this method is proposed for measuring displacements and monitoring the behavior of structural elements under constant load in field conditions. Displacements measured with a high precision LVDT sensor will be used as a benchmark for displacement calculated from RGB+D images.

This paper proposes a novel three-dimensional (3-D) geometry-based stochastic channel model (GSCM) for high-speed railway (HSR) communications in mountain scenario. The proposed model not only takes the local scatterers into consideration, but also accounts for the effect of mountains on the wireless channel, which is not considered in existing models for HSR. The mathematical representation of the channel impulse response is given in this paper. Then the cumulative distribution function (CDF) of angle of departure (AoD) and space-time correlation function (STCF) are derived based on the proposed model. Finally, some numerical results and comparisons are given.