Automating the Construction of Large-Scale Virtual Worlds

Databases for large-scale virtual worlds have several critical applications. Automating their construction can improve fidelity and save considerable time. In this article, we focus on: (1) automated cartographic feature extraction (derivation of man-made objects from aerial imagery); (2) triangulated irregular network (TIN) generation (automated techniques for terrain skin generation); and (3) road correction (automated integration of complex transportation networks). The product of these components forms a major part of the input to the final database compilation via computer image generator-specific tools such as the S1000 or the Close Combat Tactical Trainer (CCTT) database formatter. >

[1]  R. Bruce Irvin,et al.  Methods for exploiting the relationship between buildings and their shadows in aerial imagery , 1989, IEEE Trans. Syst. Man Cybern..

[2]  F. R. Norvelle Stereo correlation : window shaping and DEM corrections , 1992 .

[3]  J. Chris McGlone,et al.  Projective and object space geometry for monocular building extraction , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[4]  David M. McKeown,et al.  Cooperative methods for road tracking in aerial imagery , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  M. F. Mar,et al.  ModSAF Behavior Simulation and Control , 1993 .

[6]  R. Bruce Irvin,et al.  Methods For Exploiting The Relationship Between Buildings And Their Shadows In Aerial Imagery , 1989, Photonics West - Lasers and Applications in Science and Engineering.

[7]  Leila De Floriani,et al.  Structured graph representation of a hierarchical triangulation , 1989, Comput. Vis. Graph. Image Process..