Building Imaging

BIM
Multimodal Imaging Oriented Geometry Processing for Building Information Modelling
 
Objective:

In this project, we propose to investigate advanced acquisition, digital geometry computing, artificial intelligence and mobile technologies for multimodal image based modelling. We aim to develop a fast, smart, and mobile solution to scanning and mapping of 3D building environments, which can enhance the current BIM solution. This is inspired by recent theoretical and technical progress in several fields such as deep learning, computer vision, big data, BIM modelling, and high performance computing.

The objectives of the research are as follow.

  • To research the integration of LiDAR, photogrammetry, drone and other technology for easy-to use and efficient positioning, scanning and inspection, with emphasis on representation, consolidation, and fusion of multimodal image data;

  • To develop fundamental 3D computational models to support efficient geometric modelling, geometry analysis, multimodal data integration to enhance the building information modelling;​

  • To design efficient and fast geometric processing algorithms from multimodal images for the purpose to obtain high level salient feature information such as texture, material, and piping;

  • To research and develop solutions for intelligent and high-performance computing; and​

  • To apply the developed solutions for Building Information Modelling and simulation applications.

Value Proposition:

The research will produce a set of new algorithms, software tools and prototyping systems for processing multimodal imaging data. These software and systems lead to new IPs. The integration of them will provide an intelligent solution to scanning and positioning of 3D environments, which is aligned with BIM. The integrated and intelligent solution approach to be developed will significantly speed up the BIM cycle time compared to the current commercial practice which is mostly manual based. These techniques and the solution have commercial values. In particular, the techniques to be developed can find applications in indoor environment planning (including concealed elements), facility management, energy consumption simulation, etc.​