Temporal Octrees for Compressing Dynamic Point Cloud Streams

Marcos Slomp, Hiroshi Kawasaki, Ryo Furukawa, Ryusuke Sagawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

4 被引用数 (Scopus)

抄録

Range-based scanners built upon multiple cameras and projectors offer affordable, entire-shape and high-speed setups for 3D scanning. The point cloud streams produced by these devices require large amounts of storage space. Compressing these datasets is challenging since the capturing process may result in noise and surface irregularities, and consecutive frames can differ substantially in the overall point distribution. Exploiting spatial and temporal coherency is difficult on such conditions, but nonetheless crucial for achieving decent compression rates. This paper introduces a novel data structure, the temporal sparse voxel octree, capable of grouping spatio-temporal coherency of multiple point cloud streams into a single voxel hierarchy. In the data structure, a bit mask is attached to each node, existing nodes can then be reused at different frames by manipulating their bit masks, providing substantial memory savings. Although the technique yields some losses, the amount of loss can be controlled.

本文言語英語
ホスト出版物のタイトルProceedings - 2014 International Conference on 3D Vision Workshops, 3DV 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ49-56
ページ数8
ISBN(電子版)9781479970018
DOI
出版ステータス出版済み - 8 7 2015
外部発表はい
イベント2nd International Conference on 3D Vision Workshops, 3DV 2014 - Tokyo, 日本
継続期間: 12 8 201412 11 2014

出版物シリーズ

名前Proceedings - 2014 International Conference on 3D Vision Workshops, 3DV 2014

その他

その他2nd International Conference on 3D Vision Workshops, 3DV 2014
国/地域日本
CityTokyo
Period12/8/1412/11/14

All Science Journal Classification (ASJC) codes

  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • 放射線学、核医学およびイメージング

フィンガープリント

「Temporal Octrees for Compressing Dynamic Point Cloud Streams」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル