计算机工程 ›› 2010, Vol. 36 ›› Issue (1): 267-270.doi: 10.3969/j.issn.1000-3428.2010.01.093

• 开发研究与设计技术 • 上一篇    下一篇

基于视点的大规模点云数据实时预测调度策略

黄东晋,蓝建梁,刘 武,丁友东   

  1. (上海大学计算机工程与科学学院,上海 200072)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-01-05 发布日期:2010-01-05

Real-time Predictive Schedule Strategy for Large-scale Point-cloud Data Based on Viewpoint

HUANG Dong-jin, LAN Jian-liang, LIU Wu, DING You-dong   

  1. (School of Computer Engineering and Science, Shanghai University, Shanghai 200072)
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-01-05 Published:2010-01-05

摘要: 针对海量数据难以实时渲染的问题,提出基于视点的大规模点云数据实时预测调度策略——“5-5-5”动态调度策略。对整个三维点云进行“分区-子块化”处理,经过多分辨率压缩后保存到服务器端的数据库中。客户端根据视点的变化和菱形调度规则对子块数据进行内外存动态调度并实时绘制,同时向服务器发送传输新数据的请求。实验证明,该算法能有效解决漫游过程中的“抖动”现象,减少单次向服务器请求传输的数据量,实现漫游显示的连续性和平滑性。

关键词: 大规模点云数据, 预测调度, 抖动

Abstract: To address the problem of rendering massive data in real time difficultly, a real-time predictive schedule strategy based on viewpoint for large-scale point-cloud data is proposed, that is, “5-5-5” dynamic schedule strategy. The entire three-dimensional point-cloud is processed into “district-subblocks”. And these subblocks are saved in the server database after multi-resolution compression. According to the changes of the view parameters and diamond-shaped schedule, subblock data can be scheduled dynamically and rendered in real time. The server is asked for transmitting the data expected to the client. Experimental results show that the algorithm effectively alleviates jitters and reduces one-time transmission payload from server, with good achievement of continuity and smoothness in process of roaming.

Key words: large-scale point-cloud data, predictive schedule, jitter

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