High-precision vision-based mobile augmented reality system for context-aware architectural, engineering, construction and facility management (AEC/FM) applications

Hyojoon Bae,Jules White,Mani Golparvar-Fard

doi:10.1186/2213-7459-1-3

Abstract

Abstract Background Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment. However, these techniques primarily rely on RF-based location tracking technologies (e.g., GPS or WLAN), which typically do not provide sufficient precision in congested construction sites or require additional hardware and custom mobile devices. Method This paper presents a new vision-based mobile augmented reality system that allows field personnel to query and access 3D cyber-information on-site by using photographs taken from standard mobile devices. The system does not require any location tracking modules, external hardware attachments, and/or optical fiducial markers for localizing a user’s position. Rather, the user’s location and orientation are purely derived by comparing images from the user’s mobile device to a 3D point cloud model generated from a set of pre-collected site photographs. Results The experimental results show that 1) the underlying 3D reconstruction module of the system generates complete 3D point cloud models of target scene, and is up to 35 times faster than other state-of-the-art Structure-from-Motion (SfM) algorithms, 2) the localization time takes at most few seconds in actual construction site. Conclusion The localization speed and empirical accuracy of the system provides the ability to use the system on real-world construction sites. Using an actual construction case study, the perceived benefits and limitations of the proposed method for on-site context-aware applications are discussed in detail.

Highlights

Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment
We have proposed a new context-aware vision-based mobile augmented reality system, Hybrid 4-Dimensional Augmented Reality (HD4AR), which identifies location and orientation of field personnel solely based on a site photograph (Bae et al 2012)
To assess the ability of HD4AR to produce the initial 3D point clouds, 3D reconstruction is performed on several data sets, which were randomly collected from actual construction sites and existing buildings

Summary

Introduction

Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment. On-demand, and inexpensive access to project information on-site has significant potential to improve decision-making during construction or facility management activities This information, which is usually in the form of specifications, drawings, or schedule information, enables prompt identification, processing, and communication of discrepancies between actual and expected performance. As a part of data collection and analysis, field personnel have to carry large stacks of specifications and drawings on jobsites and spend significant amount of time to write down an actual progress on paper and compare it to relevant cyber-information (Khoury and Kamat 2009) Such inefficiencies in site analysis and information gathering can cause downtime or rework and lead to schedule delays or cost overruns. The quality and timing of information access and exchange can either delay or facilitate successful execution of on-site activities (Chen and Kamara 2011)

Methods

Results

Discussion

Conclusion