A different Manhattan project

Automatic statistical model generation

C. K. Yap, H. Biermann, A. Hertzman, C. Li, J. Meyer, H. K. Pao, T. Paxia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsR.F. Erbacher, P.C. Chen, M. Grohn, J.C. Roberts, C.M. Wittenbrink
Pages259-268
Number of pages10
Volume4665
DOIs
StatePublished - 2002
EventVisualization and Data Analysis 2002 - San Jose, CA, United States
Duration: Jan 21 2002Jan 22 2002

Other

OtherVisualization and Data Analysis 2002
CountryUnited States
CitySan Jose, CA
Period1/21/021/22/02

Fingerprint

Geographical regions
recreation
Smoke
Data structures
ground truth
smoke
Visualization
Textures
Statistical Models
stems
textures
propagation

Keywords

  • Automatic model generation
  • Large geometric model
  • Procedural model generation
  • Statistical model
  • Urban model
  • Visualization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Yap, C. K., Biermann, H., Hertzman, A., Li, C., Meyer, J., Pao, H. K., & Paxia, T. (2002). A different Manhattan project: Automatic statistical model generation. In R. F. Erbacher, P. C. Chen, M. Grohn, J. C. Roberts, & C. M. Wittenbrink (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 4665, pp. 259-268) https://doi.org/10.1117/12.458793

A different Manhattan project : Automatic statistical model generation. / Yap, C. K.; Biermann, H.; Hertzman, A.; Li, C.; Meyer, J.; Pao, H. K.; Paxia, T.

Proceedings of SPIE - The International Society for Optical Engineering. ed. / R.F. Erbacher; P.C. Chen; M. Grohn; J.C. Roberts; C.M. Wittenbrink. Vol. 4665 2002. p. 259-268.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yap, CK, Biermann, H, Hertzman, A, Li, C, Meyer, J, Pao, HK & Paxia, T 2002, A different Manhattan project: Automatic statistical model generation. in RF Erbacher, PC Chen, M Grohn, JC Roberts & CM Wittenbrink (eds), Proceedings of SPIE - The International Society for Optical Engineering. vol. 4665, pp. 259-268, Visualization and Data Analysis 2002, San Jose, CA, United States, 1/21/02. https://doi.org/10.1117/12.458793
Yap CK, Biermann H, Hertzman A, Li C, Meyer J, Pao HK et al. A different Manhattan project: Automatic statistical model generation. In Erbacher RF, Chen PC, Grohn M, Roberts JC, Wittenbrink CM, editors, Proceedings of SPIE - The International Society for Optical Engineering. Vol. 4665. 2002. p. 259-268 https://doi.org/10.1117/12.458793
Yap, C. K. ; Biermann, H. ; Hertzman, A. ; Li, C. ; Meyer, J. ; Pao, H. K. ; Paxia, T. / A different Manhattan project : Automatic statistical model generation. Proceedings of SPIE - The International Society for Optical Engineering. editor / R.F. Erbacher ; P.C. Chen ; M. Grohn ; J.C. Roberts ; C.M. Wittenbrink. Vol. 4665 2002. pp. 259-268
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