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Image-based three-dimensional (3D) reconstruction utilizes a set of photos to build 3D model and can be widely used in many emerging applications such as augmented reality (AR) and disaster recovery. Most of existing 3D reconstruction methods require a mobile user to walk around the target area and reconstruct objectives with a hand-held camera, which is inefficient and time-consuming. To meet the requirements of delay intensive and resource hungry applications in 5G, we propose an edge computing-based photo crowdsourcing (EC-PCS) framework in this paper. The main objective is to collect a set of representative photos from ubiquitous mobile and Internet of Things (IoT) devices at the network edge for real-time 3D model reconstruction, with network resource and monetary cost considerations. Specifically, we first propose a photo pricing mechanism by jointly considering their freshness, resolution and data size. Then, we design a novel photo selection scheme to dynamically select a set of photos with the required target coverage and the minimum monetary cost. We prove the NP-hardness of such problem, and develop an efficient greedy-based approximation algorithm to obtain a near-optimal solution. Moreover, an optimal network resource allocation scheme is presented, in order to minimize the maximum uploading delay of the selected photos to the edge server. Finally, a 3D reconstruction algorithm and a 3D model caching scheme are performed by the edge server in real time. Extensive experimental results based on real-world datasets demonstrate the superior performance of our EC-PCS system over the existing mechanisms. [ABSTRACT FROM AUTHOR]

High-speed railway in China has undergone rapid development in recent years. Technology for structure measurement is recognized as an important aspect of steel rail quality inspection. The shape of the rail welding base is mainly gauged using mechanical contact measurement technology. Matching this technology with the escalating demands for quality inspection of steel rails is a challenging task. In this paper, a structured light measurement approach is proposed and employed which intersects the rail through the structural light plane projected by inner and outer laser sensors. These sensors form a laser light stripe curve containing the profile information of the rail surface. By processing laser light bars using image analysis and contour reduction techniques, 3-D profiles of the rails are generated. The laser plane is fitted using the coordinate points of the laser light bars converted between the image and world coordinate systems. A new calibration method based on the parallel moving target for line-structured light is proposed to improve the calibration and address the issue caused by the limited number of the extracted calibration points during free target calibration. The rail profile, including the geometric dimension, straightness, and twist of the rail, are then measured. By comparing the measured profile with the standard contour of the rails, the rail wear can then be quantitatively assessed. The experimental results show that the proposed measurement system outperforms the traditional single index detection.

This paper focuses on the application of a multi- camera imaging system for three-dimensional (3-D) visualization and quantitative characterization of the flame front structures of a turbulent flame. The 2-D images of the flame front are captured simultaneously using identical monochromatic CCD cameras from three different directions around the flame. Dedicated computing algorithms have been developed to reconstruct the 3-D structures of the flame front using various image processing techniques such as edge detection, contour extraction, and mesh generation. A set of flame parameters, including ignition points, ignition volume, ignition surface area, and circularity, is determined from the models generated to characterize the flame front. Results obtained under a range of combustion conditions demonstrate the capability of the system for 3-D quantitative characterization of flame front structures. [ABSTRACT FROM AUTHOR]