S-LPM: segmentation augmented light-weighting and progressive meshing for the interactive visualization of large man-made Web3D models

Wen Zhou, Kai Tang, Jinyuan Jia*

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

7 Citations (Scopus)

Abstract

With the advent of the era of “big data”, increasing efforts have been focused on how to process large models to improve transmission over the internet and display in a browser, i.e., Web3D technology. Notwithstanding the many new advancements in Web3D technology, because browsers have limited storage capacity and low computational ability, the efficient display of a large model through the net remains a bottleneck problem. This paper proposes a light-weighting visualization framework, called the S-LPM framework, which includes a novel Dijkstra-based mesh segmentation operation and a new voxel-based repetition detection/removal operation to efficiently display large 3D models in a Web browser. The two key geometric operations substantially reduce the amount of data transmitted over the net, which in turn significantly increases the transmission speed. The partially transmitted data are then aligned through transformations to restore the entire original model and display it in the Web browser. The experimental results show that our approach is generally accurate and feasible, and its performance is superior to that of the benchmarking methods.

Original languageEnglish
Pages (from-to)1425-1448
Number of pages24
JournalWorld Wide Web
Volume21
Issue number5
DOIs
Publication statusPublished - 1 Sept 2018

Bibliographical note

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • Big data
  • Fine-grained scene graph
  • Light-weighting
  • Mesh segmentation
  • Repetition
  • Web3D

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