Compression of textured surfaces represented as surfel sets

T. Darom, M. R. Ruggeri, D. Saupe, N. Kiryati

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A method for lossy compression of genus-0 surfaces is presented. Geometry, texture and other surface attributes are incorporated in a unified manner. The input surfaces are represented by surfels (surface elements), i.e., by a set of disks with attributes. Each surfel, with its attribute vector, is optimally mapped onto a sphere in the sense of geodesic distance preservation. The resulting spherical vector-valued function is resampled. Its components are decorrelated by the Karhunen-Loève transform, represented by spherical wavelets and encoded using the zerotree algorithm. Methods for geodesic distance computation on surfel-based surfaces are considered. A novel efficient approach to dense surface flattening/mapping, using rectangular distance matrices, is employed. The distance between each surfel and a set of key-surfels is optimally preserved, leading to greatly improved resolution and eliminating the need for interpolation, that complicates and slows down existing surface unfolding methods. Experimental surfel-based surface compression results demonstrate successful compression at very low bit rates.

Original languageEnglish
Pages (from-to)770-786
Number of pages17
JournalSignal Processing: Image Communication
Volume21
Issue number9
DOIs
StatePublished - Oct 2006
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by the Kurt Lion Foundation. At Tel-Aviv University, it was supported by the Ministry of Science. At Konstanz University, it was supported by the DFG Graduiertenkolleg “Explorative Analysis and Visualization of Large Information Spaces”.

Funding

This research was supported by the Kurt Lion Foundation. At Tel-Aviv University, it was supported by the Ministry of Science. At Konstanz University, it was supported by the DFG Graduiertenkolleg “Explorative Analysis and Visualization of Large Information Spaces”.

FundersFunder number
Kurt Lion Foundation
Ministry of Science
Deutsche Forschungsgemeinschaft

    Keywords

    • Geodesic paths
    • Spherical mapping
    • Spherical wavelets
    • Surfels
    • Textured surface compression

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