Efficient reproduction of heritage buildings: a new way to exploit 3D point cloud slicing : An example with the Amiens Gothic Cathedral

Groux-Leclet, Dominique; Lentremy, Jérémy; Caron, Guillaume; Mouaddib, El Mustapha

doi:10.1109/digitalheritage.2018.8810106

“…Recently, PC compression (PCC) research has intensified [1]- [6] and the Motion Picture Expert Group (MPEG) is in the process of finalizing two PCC standards [7], [8], based on purely geometrical techniques (G-PCC) or on existing video compression standards (V-PCC). PCs can be used to represent three-dimensional scenes, where the points describe the hull of objects therein, and are used in, for example, autonomous navigation [9], [10], heritage preservation [11], entertainment, and telepresence [12].…”

Section: Introductionmentioning

confidence: 99%

Point Cloud Reconstruction From Truncated Geometry-Based Streams

Garcia¹,

Souto²,

Sandri³

et al. 2023

JCIS

1

0

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Geometry-based point cloud compression (G-PCC) has been rapidly evolving in the context of international standards. Despite the inherent scalability of octree-based geometry description, current G-PCC attribute compression techniques prevent full scalability for compressed point clouds. In this paper, we present a solution to add scalability to attributes compressed using the region-adaptive hierarchical transform (RAHT), enabling the reconstruction of the point cloud using only a portion of the original bitstream. Without the full geometry information, one cannot compute the weights in which the RAHT relies on to calculate its coefficients for further levels of detail. In order to overcome this problem, we propose a linear relationship approximation relating the downsampled point cloud to the truncated inverse RAHT coefficients at that same level. The linear relationship parameters are sent as side information. After truncating the bitstream at a point corresponding to a given octree level, we can, then, recreate the attributes at that level. Tests were carried out and results attest the good approximation quality of the proposed technique.

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“…Recently, PC compression (PCC) research has intensified [1]- [6] and the Motion Picture Expert Group (MPEG) is in the process of finalizing two PCC standards [7], [8], based on purely geometrical techniques (G-PCC) or on existing video compression standards (V-PCC). PCs can be used to represent 3D scenes, where the points describe the hull of objects therein, and are used in, for example, autonomous navigation [9], [10], heritage preservation [11], entertainment, and telepresence [12].…”

Section: Introductionmentioning

confidence: 99%

Point Cloud Reconstruction From Truncated Geometry-Based Streams

Garcia¹,

Souto²,

Sandri³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

Geometry-based point cloud compression (G-PCC) has been rapidly evolving in the context of international standards. Despite the inherent scalability of octree-based geometry description, current G-PCC attribute compression techniques prevent full scalability for compressed point clouds. In this paper, we present a solution to add scalability to attributes compressed using the region-adaptive hierarchical transform (RAHT), enabling the reconstruction of the point cloud using only a portion of the original bitstream. Without the full geometry information, one cannot compute the weights in which the RAHT relies on to calculate its coefficients for further levels of detail. In order to overcome this problem, we propose a linear relationship approximation relating the downsampled point cloud to the truncated inverse RAHT coefficients at that same level. The linear relationship parameters are sent as side information. After truncating the bitstream at a point corresponding to a given octree level, we can, then, recreate the attributes at that level. Tests were carried out and results attest the good approximation quality of the proposed technique.

show abstract