Dynamic compression of curve-based point cloud

  • Authors:

  • Ismael Daribo;Ryo Furukawa;Ryusuke Sagawa;Hiroshi Kawasaki;Shinsaku Hiura;Naoki Asada

  • Affiliations:

  • Faculty of Information Sciences, Hiroshima City University, Hiroshima, Japan;Faculty of Information Sciences, Hiroshima City University, Hiroshima, Japan;National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan;Faculty of Engineering, Kagoshima University, Kagoshima, Japan;Faculty of Information Sciences, Hiroshima City University, Hiroshima, Japan;Faculty of Information Sciences, Hiroshima City University, Hiroshima, Japan

  • Venue:
  • PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
  • Year:
  • 2011

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Abstract

With the increasing demands for highly detailed 3D data, dynamic scanning systems are capable of producing 3D+t (a.k.a. 4D) spatio-temporal models with millions of points recently. As a consequence, effective 4D geometry compression schemes are required to face the need to store/transmit the huge amount of data, in addition to classical static 3D data. In this paper, we propose a 4D spatio-temporal point cloud encoder via a curve-based representation of the point cloud, particularly well-suited for dynamic structured-light-based scanning systems, wherein a grid pattern is projected onto the surface object. The object surface is then naturally sampled in a series of curves, due to the grid pattern. This motivates our choice to leverage a curve-based representation to remove the spatial and temporal correlation of the sampled point along the scanning directions through a competitive-based predictive encoder that includes different spatio-temporal prediction modes. Experimental results show the significant gain obtained with the proposed method.