Modeling and visualizing the cultural heritage data set of Graz

The inner city (Old Town) of Graz will be the European cultural capital in 2003. In this paper we present preliminary results on the reconstruction and visualization of this kind of cultural heritage data. Starting with a simple block model obtained by converting 2 1/2 dimensional GIS (geographic information system) data we focus on the image based modeling of the facades. Herein we illustrate a robust search for corresponding points to estimate the relative orientation between image pairs.Additional, we outline our real-time rendering approach based on a LOD-R-tree concept. Special attention is paid on the LOD (level of detail) generation for historic buildings where two different ways working in 2D and 3D are explained. The visualization system is communicating asynchronously with a database system storing the LOD-R-tree data structure. This client-server configuration provides interactive navigation through the virtual scene and the scalability of a database management system.

[1]  F. Thiemann.  GENERALIZATION OF 3 D BUILDING DATA , 2002 .

[2]  M. Garland,et al.  Multiresolution Modeling: Survey & Future Opportunities , 1999 .

[3]  Dinesh Manocha,et al.  Simplification envelopes , 1996, SIGGRAPH.

[4]  Reinhard Koch,et al.  Three-dimensional scene reconstruction from images , 2000, Electronic Imaging.

[5]  Reinhard Klein,et al.  Mesh reduction with error control , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[6]  Andrew Zisserman,et al.  From Images to Virtual and Augmented Reality , 2000, Confluence of Computer Vision and Computer Graphics.

[7]  Bill Triggs,et al.  Autocalibration from Planar Scenes , 1998, ECCV.

[8]  J. Biemond,et al.  Correspondence estimation in image pairs , 1999, IEEE Signal Process. Mag..

[9]  Joachim Bauer,et al.  Multiresolution texture for photorealistic rendering , 2001, Proceedings Spring Conference on Computer Graphics.

[10]  Antonin Guttman,et al.  R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.

[11]  Dieter Schmalstieg,et al.  Smooth levels of detail , 1997, Proceedings of IEEE 1997 Annual International Symposium on Virtual Reality.

[12]  Takeo Kanade,et al.  Image-consistent surface triangulation , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[13]  Helmut Mayer,et al.  SCALE-SPACE EVENTS FOR THE GENERALIZATION OF 3D-BUILDING DATA , 2000 .

[14]  Gabriel Taubin,et al.  Geometric compression through topological surgery , 1998, TOGS.

[15]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[16]  Hugues Hoppe,et al.  Progressive meshes , 1996, SIGGRAPH.

[17]  Paolo Cignoni,et al.  Multiresolution decimation based on global error , 1996, The Visual Computer.

[18]  Carlo H. Séquin,et al.  Adaptive display algorithm for interactive frame rates during visualization of complex virtual environments , 1993, SIGGRAPH.

[19]  Michael Garland,et al.  Multiresolution Modeling: Survey and Future Opportunities , 1999, Eurographics.

[20]  Peter Shirley,et al.  Visual navigation of large environments using textured clusters , 1995, I3D '95.

[21]  Paolo Cignoni,et al.  A comparison of mesh simplification algorithms , 1998, Comput. Graph..

[22]  James H. Clark,et al.  Hierarchical geometric models for visible surface algorithms , 1976, CACM.

[23]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[24]  Václav Hlavác,et al.  Consistent Projective Reconstruction from Multiple Views , 2000, Confluence of Computer Vision and Computer Graphics.