Building environment information modeling based on multi-view image
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(1.School of Architecture, Harbin Institute of Technology, Harbin 150001, China; 2. Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology (Harbin Institute of Technology), Ministry of Industry and Information Technology, Harbin 150001, China)

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TU87

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    Abstract:

    Combined with practical cases, this paper explores the modeling method of building environment information based on multi-view images, aiming to improve the efficiency of building environment information modeling and the accuracy of local information modeling of building environment such as eave bottom. The technical route of multi-view image fusion was investigated, low altitude photogrammetry and ground photography were carried out based on practical cases, and the architectural and environmental image data of the practical cases were collected. By constructing connection points and fusing multi-view image data, the ground image was fused with aerial image, and the image of some dead corner areas which are difficult to capture in the air was obtained to realize multi-angle and omni-directional image acquisition. Through the air triangulation processing, dense matching, and texture mapping, the three-dimensional digital model of the building environment information of the practical case was generated. Results show that the integration of low altitude photogrammetry and ground photography image data could significantly improve the modeling efficiency of building environment information and the modeling accuracy of building detail information, and could solve the problem of incomplete information collected by a single image source, which has the advantages of low cost, high efficiency, and easy operation. In the process of data collection and protection of preserved buildings, the proposed method can achieve the rapid and efficient preservation and recording of three-dimensional data as well as realize the preservation and inheritance of multi-dimensional data of historical buildings.

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History
  • Received:January 11,2020
  • Revised:
  • Adopted:
  • Online: January 29,2021
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