ISSN:
1573-9724
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Abstract An approach to automatically extract three dimensional (3D) models (that is, geometries and topologies) of physical objects in a facility is described. The rationale for this work is its repeated use in efficiently developing databases of 3D objects for applying virtual reality (VR) tools in detailed layout decision support. Obtaining 3D object models can be a challenging task. Sometimes they are available, for example, in a Computer-Aided Design (CAD) database and these can be readily imported into a VR database. But on many occasions one is not so fortunate and these object models have to be created in correlation to an existing or proposed facility, which can be an extremely tedious and time consuming task. A time efficient and economical alternative is to use video camera images, but quickly and accurately capturing the depth information from 2D camera images has so far remained elusive because the existing methodologies are too general purpose and operate at a lower level of abstraction, namely digitized images. We have developed a method for directly inputting 3D objects into VR-aided facility layout models, by integrating the strengths of previously tried and tested technological components: (i) camera calibration; (ii) image processing; (iii) stereo vision; and (iv) Delaunay triangulation. The techniques described here are embedded in a prototype architecture and toolkit called MIRRORS (Methodology for Inputting Raw Recordings into 3D Object Renderings for Stereo). The primary contribution of this paper is that it has been able to design an integrated system to build 3D object models from 2D images. The MIRRORS system has been primarily designed for objects without free-form surfaces and whose shape can be recovered from a relatively nondense set of points.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1007586110265
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