Edition-Oriented 3D Model Rebuilt from Photography

Joaquim Silvestre , François Guéna , Yasushi Ikeda

The topic of this paper is about a technique to turn pictures into an intuitively modifiable 3D model. The research employs an analytical method using algorithms to conceptualise and digital-ise architectural spaces in order to highlight parametric shapes. Usually , from one group of digital photos, photogrammetry techniques produce a 3D-model mesh through a high-density 3D point cloud. This discordance between our intuitive partitioning of the mesh and its bare polygonal structure makes it interact poorly compared to the af-fordance of shape and component in our daily experience. Through a capture device, a visualisation of architecture in a digital data form is produced. They are processed by computer vision algorithms and machine learning systems in order to be refined into a parametric model. Parametric elements can be described as a compound of formulas and parameters. By keeping the formula and changing the parameters, these elements can be easily modified in a range of likenesses. After being detected during scans, these shapes can be adapted to fit the intention of the designer during the design phase.

Mots clés: 3D model; convolutional neural network; Photogrammetry; design tool

Domaines: Modélisation et simulation

Joaquim Silvestre, François Guéna, Yasushi Ikeda. Edition-Oriented 3D Model Rebuilt from Photography. 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia CAADRIA 2016, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Mar 2016, Melbourne, Australia. pp.445 - 454. ⟨hal-02546053⟩