Abstract: Disclosed is a graphics system and associated methodologies for selectively increasing the level-of-detail at specific parts of a mesh model based on a point cloud that provides a higher detailed representation of the same or similar three-dimensional (“3D”) object. The graphics system receives the mesh model and the point cloud of the 3D object. The graphics system determines a region-of-interest of the 3D object based in part on differences amongst points that represent part or all of the region-of-interest. The graphics system reconstructs the region-of-interest in the mesh model and generates a modified mesh model by modifying a first set of meshes representing the region-of-interest in the mesh model to a second set of meshes based on the positional elements of the point cloud points. The second set of meshes has more meshes and represents the region-of-interest at a higher level-of-detail than the first set of meshes.

Abstract: Disclosed is a graphics system and associated methodologies for selectively increasing the level-of-detail at specific parts of a mesh model based on a point cloud that provides a higher detailed representation of the same or similar three-dimensional (“3D”) object. The graphics system receives the mesh model and the point cloud of the 3D object. The graphics system determines a region-of-interest of the 3D object based in part on differences amongst points that represent part or all of the region-of-interest. The graphics system reconstructs the region-of-interest in the mesh model and generates a modified mesh model by modifying a first set of meshes representing the region-of-interest in the mesh model to a second set of meshes based on the positional elements of the point cloud points. The second set of meshes has more meshes and represents the region-of-interest at a higher level-of-detail than the first set of meshes.

Abstract: Disclosed is a graphics system and associated methodologies for selectively increasing the level-of-detail at specific parts of a mesh model based on a point cloud that provides a higher detailed representation of the same or similar three-dimensional (“3D”) object. The graphics system receives the mesh model and the point cloud of the 3D object. The graphics system determines a region-of-interest of the 3D object based in part on differences amongst points that represent part or all of the region-of-interest. The graphics system reconstructs the region-of-interest in the mesh model and generates a modified mesh model by modifying a first set of meshes representing the region-of-interest in the mesh model to a second set of meshes based on the positional elements of the point cloud points. The second set of meshes has more meshes and represents the region-of-interest at a higher level-of-detail than the first set of meshes.

Abstract: A system prioritizes the rendering and streaming of image data based on risk maps that predict change in a three-dimensional (“3D”) environment. The system receives primitives that are distributed across a 3D space to represent the 3D environment. The system generates a first image based on primitives that fall within a first view frustum, and generates a risk map with a risk value for each particular pixel of the first image. Each risk value quantifies a probability that a pixel of the first image associated with that risk value changes as a result of changing the first view frustum to a second view frustum. The system then performs an out-of-order rendering of primitives that fall within the second view frustum based on the risk value for each first image pixel that is replaced in a second image with a rendered primitive from the second view frustum.

Abstract: A system prioritizes the rendering and streaming of image data based on risk maps that predict change in a three-dimensional (“3D”) environment. The system receives primitives that are distributed across a 3D space to represent the 3D environment. The system generates a first image based on primitives that fall within a first view frustum, and generates a risk map with a risk value for each particular pixel of the first image. Each risk value quantifies a probability that a pixel of the first image associated with that risk value changes as a result of changing the first view frustum to a second view frustum. The system then performs an out-of-order rendering of primitives that fall within the second view frustum based on the risk value for each first image pixel that is replaced in a second image with a rendered primitive from the second view frustum.