Abstract: Provided are an apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, and more particularly, to an apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, in which three-dimensional modeling data of a building structure may be quickly and conveniently reversely modeled by using a plurality of photographic images. According to the apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, three-dimensional modeling data of a building structure may be reversely modeled by using photographic images of the building structure captured using a camera, at low costs and quickly and easily, thereby remarkably increasing the productivity of the manufacture of a building information model (BIM).

Abstract: Provided are an apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, and more particularly, to an apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, in which three-dimensional modeling data of a building structure may be quickly and conveniently reversely modeled by using a plurality of photographic images. According to the apparatus and method of three-dimensional reverse modeling of a building structure by using photographic images, three-dimensional modeling data of a building structure may be reversely modeled by using photographic images of the building structure captured using a camera, at low costs and quickly and easily, thereby remarkably increasing the productivity of the manufacture of a building information model (BIM).

Abstract: Programmatic extraction and management of solid and surface modeling parameters from raw 3D scan data is discussed. An automated process reads raw 3D scan data and works in communication with a CAD system able to perform CAD part modeling. The user is provided with an automatic function to segment a mesh model (formed from the raw 3D scan data) into dozens of mesh regions. A graphical user interface is provided which enables a user to choose a type of the design intent along with the mesh regions from which the design intent is calculated. Each design intent is represented in a vector, a plane or a poly-line depending upon the type of design intent. In response to a user demand for the parameters of a modeling feature, a best approximation of the requested parameter value is calculated by processing the raw 3D scan data using a set of functions.

Abstract: A mechanism for automatically calculating loft surfaces from raw 3D scan data represented as a mesh or point cloud model is discussed. Users enter parameters related to the loft surface calculation via a provided user interface. User input and/or programmatically calculated parameters may include U-V direction, guide curve identification, and the amount of allowable deviation error between the calculated loft surface and the 3D scan data. Profile curves meeting the given parameters are then generated and a loft surface is calculated using the generated profile curves for a selected region. The user may select geometrically separated regions in order to create a single loft surface that connects the separate regions.

Abstract: Programmatic extraction and management of solid and surface modeling parameters from raw 3D scan data is discussed. An automated process reads raw 3D scan data and works in communication with a CAD system able to perform CAD part modeling. The user is provided with an automatic function to segment a mesh model (formed from the raw 3D scan data) into dozens of mesh regions. A graphical user interface is provided which enables a user to choose a type of the design intent along with the mesh regions from which the design intent is calculated. Each design intent is represented in a vector, a plane or a poly-line depending upon the type of design intent. In response to a user demand for the parameters of a modeling feature, a best approximation of the requested parameter value is calculated by processing the raw 3D scan data using a set of functions.