Efficient Approximate Visibility Query in Large Dynamic Environments

Visibility query is fundamental to many analysis and decision-making tasks in virtual environments. Visibility computation is time complex and the complexity escalates in large and dynamic environments, where the visibility set (i.e., the set of visible objects) of any viewpoint is probe to change at any time. However, exact visibility query is rarely necessary. Besides, it is inefficient, if not infeasible, to obtain the exact result in a dynamic environment. In this paper, we formally define an Approximate Visibility Query (AVQ) as follows: given a viewpoint v, a distance e and a probability p, the answer to an AVQ for the viewpoint v is an approximate visibility set such that its difference with the exact visibility set is guaranteed to be less than e with confidence p. We propose an approach to correctly and efficiently answer AVQ in large and dynamic environments. Our extensive experiments verified the efficiency of our approach.

[1]  Vlastimil Havran,et al.  Hierarchical visibility culling with occlusion trees , 1998, Proceedings. Computer Graphics International (Cat. No.98EX149).

[2]  Gavin S. P. Miller,et al.  Hierarchical Z-buffer visibility , 1993, SIGGRAPH.

[3]  Craig Gotsman,et al.  Output-senstitive rendering and communication in dynamic virtual environments , 1997, VRST '97.

[4]  Frederick P. Brooks,et al.  Towards image realism with interactive update rates in complex virtual building environments , 1990, I3D '90.

[5]  Mukesh K. Mohania,et al.  Advances in Databases: Concepts, Systems and Applications , 2007 .

[6]  David A. Forsyth,et al.  View-dependent culling of dynamic systems in virtual environments , 1997, SI3D.

[7]  Hanan Samet,et al.  Foundations of multidimensional and metric data structures , 2006, Morgan Kaufmann series in data management systems.

[8]  Lidan Shou,et al.  HDoV-tree: the structure, the storage, the speed , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[9]  Lidan Shou,et al.  Walking Through a Very Large Virtual Environment in Real-time , 2001, VLDB.

[10]  Michael H. Böhlen,et al.  iTopN: incremental extraction of the N most visible objects , 2003, CIKM '03.

[11]  Ken C. K. Lee,et al.  Nearest Surrounder Queries , 2006, IEEE Transactions on Knowledge and Data Engineering.

[12]  William V. Baxter,et al.  HLODs for faster display of large static and dynamic environments , 2001, I3D '01.

[13]  Michael Gervautz,et al.  R-trees for organizing and visualizing 3D GIS databases , 2000 .

[14]  Rui Zhang,et al.  Visible Nearest Neighbor Queries , 2007, DASFAA.

[15]  Yossi Matias,et al.  Fast incremental maintenance of approximate histograms , 1997, TODS.

[16]  Harlen Costa Batagelo,et al.  Dynamic scene occlusion culling using a regular grid , 2002, Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing.

[17]  Carlo H. Séquin,et al.  Visibility preprocessing for interactive walkthroughs , 1991, SIGGRAPH.

[18]  Frédo Durand,et al.  A Survey of Visibility for Walkthrough Applications , 2003, IEEE Trans. Vis. Comput. Graph..