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3 D Computer Modeling with Intra Component, Geometric, Quality and Topological Constraints.

Title: 3 D Computer Modeling with Intra Component, Geometric, Quality and Topological Constraints.
Authors: Styliadis, Athanasios D.; Patias, Petros G.; Zestas, Nikos C.
Source: Informatica; 2003, Vol. 14 Issue 3, p375-392, 18p
Abstract: The study of 3 D indoor accurate scenery modeling is an active research area. The produced model can be used in a number of virtual reality applications, in digital documentation of monuments and sites, and so on. Digital photogrammetry and CAD technology have to play a vital role in this field. Photogrammetry's contribution is mainly on data acquisition from imagery, whilst the necessary image knowledge is derived from geometry and topology of image contents. While the first is traditionally used, the second one only lately is been tackled. In this paper, a technique is presented for modeling of indoor scenery based on digital images, photo derived intra component, geometric and topologic constraints, object oriented graphic databases containing 3 D parametric models and a rough (generic) CAD model. Optionally, an absolute reference system could be applied, but for VR applications a relative reference system is adequate. The original contribution with respect to related works in this field is mainly the introduction of Display File, Segment Table, Scene Parts Table and Constraint Table structures which deal with the constraints and “drive” a modeling control program called the Constraint Modeler. The use of these structures leads in a direct, global, portable, and semi automated technique for 3 D indoor modeling. Experimental results from simulated images are presented, and the robustness of the technique is discussed. [ABSTRACT FROM AUTHOR]
: Copyright of Informatica is the property of Vilnius University, Institute of Data Science & Digital Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index