Abstract: A method and apparatus for compressing three-dimensional point cloud data is disclosed. In one aspect, a method for compressing three dimensional point cloud includes steps of retrieving three-dimensional point cloud data; providing one or more grids to the three-dimensional point cloud data; assigning one binary digit to each three-dimensional grid voxel containing said point cloud data and assigning the other binary digit to each three-dimensional grid voxel that does not have said point cloud data; converting the three-dimensional grid into two-dimensional tiles; and storing information of a plurality of binary strings in said two-dimensional tiles. In one embodiment, the step of storing information of a plurality of binary strings in said two-dimensional tiles includes a step of storing the number of repeating times of each binary digit in the binary strings. The method can significantly reduce memory space, as well as preserving small details of the point cloud.

Abstract: This invention relates to a method and apparatus for accurate compression and decompression of data. More specifically, this invention relates to a method and apparatus for compressing three dimensional spatial points (so called “point cloud”) and decompressing such data to produce an accurate point cloud. In one embodiment of the present invention, a level set based method is used to reconstruct a surface to approximate the surface of the point cloud. This reconstructed surface is defined implicitly as the zero level set of a function, which can be computed on a regular three-dimensional rectangular grid. Furthermore, the three-dimensional grid may be rearranged into a two-dimensional grid where the data are compressed and stored in a form of gradient. In order to recover the point cloud, the three-dimensional grid is rebuilt from the two-dimensional data and an interpolating algorithm on the implicit function is utilized to compute the points on the surface.

Abstract: A method and apparatus for compressing three-dimensional point cloud data is disclosed. In one aspect, a method for compressing three dimensional point cloud includes steps of retrieving three-dimensional point cloud data; providing one or more grids to the three-dimensional point cloud data; assigning one binary digit to each three-dimensional grid voxel containing said point cloud data and assigning the other binary digit to each three-dimensional grid voxel that does not have said point cloud data; converting the three-dimensional grid into two-dimensional tiles; and storing information of a plurality of binary strings in said two-dimensional tiles. In one embodiment, the step of storing information of a plurality of binary strings in said two-dimensional tiles includes a step of storing the number of repeating times of each binary digit in the binary strings. The method can significantly reduce memory space, as well as preserving small details of the point cloud.

Abstract: This invention relates to a method and apparatus for accurate compression and decompression of data. More specifically, this invention relates to a method and apparatus for compressing three dimensional spatial points (so called “point cloud”) and decompressing such data to produce an accurate point cloud. In one embodiment of the present invention, a level set based method is used to reconstruct a surface to approximate the surface of the point cloud. This reconstructed surface is defined implicitly as the zero level set of a function, which can be computed on a regular three-dimensional rectangular grid. Furthermore, the three-dimensional grid may be rearranged into a two-dimensional grid where the data are compressed and stored in a form of gradient. In order to recover the point cloud, the three-dimensional grid is rebuilt from the two-dimensional data and an interpolating algorithm on the implicit function is utilized to compute the points on the surface.