Abstract: A splat generation system directly generates splats to accurately represent a three-dimensional (3D) object or scene from existing 3D image data or 3D primitives of a different non-splat 3D format without multiple iterative passes through a neural network or machine learning process. The system receives the 3D primitives of the non-splat 3D format, selects a set of 3D primitives, generates one or more splats that form a first surface that matches a second surface formed by the set of 3D primitives with an acceptable amount of structural loss, and defines visual characteristics for the one or more splats to match visual characteristics across the surface formed by the set of 3D primitives with an acceptable amount of visual characteristic loss. The system present the one or more splats instead of the set of 3D primitives in response to a request to access the 3D object or scene.

Abstract: An optimization system reduces the data encoded within a point cloud for streaming and/or rendering of a lossy representation of the point cloud. The optimization system generates a first optimized splat for a first visual characteristic of the point cloud by replacing a first set of points having a first common value for the first visual characteristic with a first replacement primitive, and generates a second optimized splat for a second visual characteristic of the point cloud by replacing a second set of points having a second common value for the second visual characteristic with a second replacement primitive. The optimization system provides the first optimized splat and the second optimized splat instead of the original points of the point cloud in response to a request to access the point cloud.

Abstract: An optimization system reduces the data encoded within a point cloud for streaming and/or rendering of a lossy representation of the point cloud. The optimization system generates a first optimized splat for a first visual characteristic of the point cloud by replacing a first set of points having a first common value for the first visual characteristic with a first replacement primitive, and generates a second optimized splat for a second visual characteristic of the point cloud by replacing a second set of points having a second common value for the second visual characteristic with a second replacement primitive. The optimization system provides the first optimized splat and the second optimized splat instead of the original points of the point cloud in response to a request to access the point cloud.

Abstract: A distribution system adaptively provides different lossy encodings for different views of a point cloud to a client device based on network or rendering performance of the client device. The distribution system receives a request to access the point cloud, and determines the one or more performance parameters that limit an amount of the point cloud data that the client device is able to receive or process in a given time. The distribution system selects and provides the client device with different sets of optimized splats for different views of the point cloud that satisfy the one or more performance parameters based on a cumulative amount of data encoded within the different sets of optimized splats being equal to or less than the amount of point cloud data that the client device is able to receive or process in the given time.

Abstract: A splat compression system and associated methods are provided to efficiently compress and decompress data of a three-dimensional (3D) splat representation using textures so that the size of the splat representation is reduced with minimal loss in fidelity. The compression includes receiving the splats that make up the 3D splat representation, determining clusters that are associated with a different set of the splats that are positioned about a different common plane, and defining each cluster with a position based on the positional data from the different set of splats associated with that cluster. The compression includes converting the positional data from the different set of splats associated with each cluster to offsets from the position of the associated cluster, and generating the compressed 3D representation with a definition for each cluster and a texture that stores the offsets for the different set of splats associated with each cluster.

Abstract: An optimization system reduces the data encoded within a point cloud for streaming and/or rendering of a lossy representation of the point cloud. The optimization system generates a first optimized splat for a first visual characteristic of the point cloud by replacing a first set of points having a first common value for the first visual characteristic with a first replacement primitive, and generates a second optimized splat for a second visual characteristic of the point cloud by replacing a second set of points having a second common value for the second visual characteristic with a second replacement primitive. The optimization system provides the first optimized splat and the second optimized splat instead of the original points of the point cloud in response to a request to access the point cloud.

Abstract: An optimization system reduces the data encoded within a point cloud for streaming and/or rendering of a lossy representation of the point cloud. The optimization system generates a first optimized splat for a first visual characteristic of the point cloud by replacing a first set of points having a first common value for the first visual characteristic with a first replacement primitive, and generates a second optimized splat for a second visual characteristic of the point cloud by replacing a second set of points having a second common value for the second visual characteristic with a second replacement primitive. The optimization system provides the first optimized splat and the second optimized splat instead of the original points of the point cloud in response to a request to access the point cloud.