3D WALK-THROUGH ENVIRONMENTAL MODEL FOR VISUALIZATION OF INTERIOR CONSTRUCTION PROGRESS MONITORING

  • Seungjun Roh (Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Feniosky Pena-Mora (University of Illinois at Urbana-Champaign)
  • Published : 2009.05.27

Abstract

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.

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Acknowledgement

We would like to thank Turner, Gilbane, Williams Brothers, and Grunloh Construction companies as well as University of Illinois Housing and Facilities and Services for their contributions to this research project. This work was financially supported by National Science Foundation Award No. CMMI-0800500.