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Published July 2000 | public
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Progressive geometry compression

Khodakovsky, Andrei
Schröder, Peter ORCID icon
Sweldens, Wim
Others:
Brown, Judith R.
Akeley, Kurt
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Abstract

We propose a new progressive compression scheme for arbitrary topology, highly detailed and densely sampled meshes arising from geometry scanning. We observe that meshes consist of three distinct components: geometry, parameter, and connectivity information. The latter two do not contribute to the reduction of error in a compression setting. Using semi-regular meshes, parameter and connectivity information can be virtually eliminated. Coupled with semi-regular wavelet transforms, zerotree coding, and subdivision based reconstruction we see improvements in error by a factor four (12dB) compared to other progressive coding schemes.

Additional Information

© 2002 ACM Press. Andrei Khodakovsky was partially supported through an internship at Lucent Technologies. Other support came from NSF (ACI-9624957, ACI-9721349, DMS-9872890, DMS-9874082), Alias|Wavefront, a Packard Fellowship, and the SGI-Utah Visual Supercomputing Center. Special thanks to Cici Koenig, Igor Guskov, Mathieu Desbrun, Aaron Lee, and Martin Vetterli. Datasets are courtesy Cyberware, the Stanford program in Computer Graphics and Hugues Hoppe. Our implementation uses an arithmetic coder of Geoff Davis and John Danskin. We are particularly grateful to Renato Pajarola, Craig Gotsman, and Gabriel Taubin for providing us with executables of their mesh compression algorithms.

Additional details

Identifiers Funding Dates
Created:
August 19, 2023
Modified:
October 23, 2023