Patent classifications
G06T17/005
Method for Generating a Hierarchical Data Structure, Hierarchical Data Structure, and Method for Streaming Three-Dimensional Objects
The present invention relates to a method for generating a hierarchical data structure of a three-dimensional object, such a hierarchical data structure, and a method for streaming three-dimensional objects. In the method according to the invention, a hierarchical data structure is generated from a three-dimensional object, which has and possibly consists of three-dimensional object data and a texture that is mapped onto the object data, by first converting the three-dimensional object data into multiple detail levels and then segmenting the detail levels, wherein the texture is respectively mapped onto the segments with a corresponding resolution.
Storage of levels for bottom level bounding volume hierarchy
Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may configure a BVH structure including a plurality of levels and a plurality of nodes, the BVH structure being associated with geometry data for a plurality of primitives in a scene. The apparatus may also identify an amount of storage in a GMEM that is available for storing at least some of the plurality of nodes in the BVH structure. Further, the apparatus may allocate the BVH structure into a first BVH section including a plurality of first nodes and a second BVH section including a plurality of second nodes. The apparatus may also store first data associated with the plurality of first nodes in the GMEM and second data associated with the plurality of first nodes and the plurality of second nodes in a system memory.
Depth codec for real-time, high-quality light field reconstruction
Techniques to facilitate compression of depth data and real-time reconstruction of high-quality light fields. A parameter space of values for a line, pairs of endpoints on different sides of the line, and a palette index for each pixel of a pixel tile of a depth image is sampled. Values for the line, the pairs of endpoints, and the palette index that minimize an error are determined and stored.
Three-dimensional data creation method, three-dimensional data transmission method, three-dimensional data creation device, and three-dimensional data transmission device
A three-dimensional data creation method includes: creating first three-dimensional data from information detected by a sensor; receiving encoded three-dimensional data that is obtained by encoding second three-dimensional data; decoding the received encoded three-dimensional data to obtain the second three-dimensional data; and merging the first three-dimensional data with the second three-dimensional data to create third three-dimensional data.
Map reports from vehicles in the field
Aspects of the present disclosure relate generally to systems and methods for assessing validity of a map using image data collected by a laser sensor along a vehicle path. The method may compile image data received from the laser sensor. The map subject to assessment may define an area prohibiting entry by a vehicle.
Hierarchies to generate animation control rigs
An animation system is provided for generating an animation control rig for character development, configured to manipulate a skeleton of an animated character. Hierarchical representation of puppets includes groups of functions related in a hierarchy according to character specialization for creating the animated rig are derived using base functions of a core component node. The hierarchical nodes may include an archetype node, at least one appendage node, and at least one feature node. In some implementations, portions of a hierarchical node, including the functions from the core component node, may be shared to generate different animation rigs for a variety of characters. In some implementations, portions of a hierarchical node, including the component node functions, may be reused to build similar appendages of a same animation rig.
VOXELIZATION OF A 3D STRUCTURAL MEDICAL IMAGE OF A HUMAN'S BRAIN
A computer-implemented method for voxelizing a 3D structural medical image of a human's brain. The method including obtaining a 3D structural medical image of the human's brain, including a reference frame, generating a voxelized 3D structural medical image, obtaining parameters of at least one EEG electrode sensor and, for each EEG electrode sensor: a localization in the voxelized 3D structural medical image's reference frame, and a sensor detection distance, obtaining a regular 3D grid of voxels, and for each voxel of the 3D grid, iteratively subdividing the voxel while the distance between the voxel and the localization of any electrode sensor is smaller than or equal to the sensor detection distance and while a size of the voxel is greater than a predetermined length, each subdivided voxel joining a finite number of voxels of the voxelized 3D structural medical image.
TECHNIQUES FOR INTRODUCING ORIENTED BOUNDING BOXES INTO BOUNDING VOLUME HIERARCHY
Described herein is a technique for modifying a bounding volume hierarchy. The techniques include combining preferred orientations of child nodes of a first bounding box node to generate a first preferred orientation; based on the first preferred orientation, converting one or more child nodes of the first bounding box node into one or more oriented bounding box nodes; combining preferred orientations of child nodes of a second bounding box node to generate a second preferred orientation; and based on the second preferred orientation, maintaining one or more children of the second bounding box node as non-oriented bounding box nodes.
Octree-based convolutional neural network
The implementations of the subject matter described herein relate to an octree-based convolutional neural network. In some implementations, there is provided a computer-implemented method for processing a three-dimensional shape. The method comprises obtaining an octree for representing the three-dimensional shape. Nodes of the octree include empty nodes and non-empty nodes. The empty nodes exclude the three-dimensional shape and are leaf nodes of the octree, and the non-empty nodes include at least a part of the three-dimensional shape. The method further comprises for nodes in the octree with a depth associated with a convolutional layer of a convolutional neural network, performing a convolutional operation of the convolutional layer to obtain an output of the convolutional layer.
Spatial partitioning for graphics rendering
An improved virtual environment creation and testing process can be achieved by a combination of spatial partitioning and reverse tree generation. The reverse tree may be representative of the virtual environment and may be generated starting from a smallest portion or zone of the virtual environment (represented as a leaf node) and expanding up towards a root node representative of the entire virtual environment. Advantageously, the system can add new zones to the virtual environment and representative tree data structure that are external to the existing virtual environment without generating a new tree data structure. Thus, the computing resources utilized by the system disclosed herein may be significantly reduced compared to existing processes while improving the flexibility of the spatial partitioning and tree generation process thereby enabling spatial partitioning to be performed in real or near real time as a developer authors the virtual environment.