TY - GEN
T1 - Dynamic compression of curve-based point cloud
AU - Daribo, Ismael
AU - Furukawa, Ryo
AU - Sagawa, Ryusuke
AU - Kawasaki, Hiroshi
AU - Hiura, Shinsaku
AU - Asada, Naoki
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=82155191348&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-25346-1_29
DO - 10.1007/978-3-642-25346-1_29
M3 - Conference contribution
AN - SCOPUS:82155191348
SN - 9783642253454
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 323
EP - 334
BT - Advances in Image and Video Technology - 5th Pacific Rim Symposium, PSIVT 2011, Proceedings
T2 - 5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011
Y2 - 20 November 2011 through 23 November 2011
ER -