An Edge Computing-based Photo Crowdsourcing Framework for Real-time 3D Reconstruction

TL;DR

This paper introduces an edge computing framework for real-time 3D reconstruction using photos from mobile and IoT devices, optimizing photo selection, pricing, and network resources for efficiency and cost-effectiveness.

Contribution

The paper proposes a novel EC-PCS framework with a photo pricing mechanism, a dynamic photo selection scheme, and an optimal network resource allocation method for real-time 3D reconstruction.

Findings

Outperforms existing mechanisms in real-world datasets

Achieves near-optimal photo selection with a greedy algorithm

Reduces maximum uploading delay through resource allocation

Abstract

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.