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    METHODS, SYSTEMS AND APPARATUS TO IMPROVE SPATIAL-TEMPORAL DATA MANAGEMENT
    44.
    发明申请
    METHODS, SYSTEMS AND APPARATUS TO IMPROVE SPATIAL-TEMPORAL DATA MANAGEMENT 有权

    公开(公告)号：US20220067012A1

    公开(公告)日：2022-03-03

    申请号：US17228864

    申请日：2021-04-13

    Applicant: Intel Corporation

    Inventor： David I. Gonzalez Aguirre ,  Ignacio J. Alvarez ,  Javier Felip Leon

    IPC: G06F16/22 ,  G06F16/2458 ,  G06F16/23

    Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve spatial-temporal data management. An example apparatus includes a hypervoxel data structure generator to generate a root hexatree data structure having sixteen hypernodes, an octree manager to improve a spatiotemporal data access efficiency by generating a first degree of symmetry in the root hexatree, the octree manager to assign a first portion of the hypernodes to a positive temporal subspace and to assign a second portion of the hypernodes to a negative temporal subspace, and a quadtree manager to improve the spatiotemporal data access efficiency by generating a second degree of symmetry in the root hexatree, the quadtree manager to assign respective hypernodes of the positive temporal subspace and the negative temporal subspace to respective positive and negative spatial subspaces.

    METHODS AND APPARATUS TO IMPLEMENT A NEURAL NETWORK
    45.
    发明申请
    METHODS AND APPARATUS TO IMPLEMENT A NEURAL NETWORK 有权

    公开(公告)号：US20210150323A1

    公开(公告)日：2021-05-20

    申请号：US17133181

    申请日：2020-12-23

    Applicant: Intel Corporation

    Inventor： Javier Sebastian Turek ,  Ignacio J. Alvarez ,  David Israel Gonzalez Aguirre ,  Javier Felip Leon ,  Maria Soledad Elli

    IPC: G06N3/063 ,  G06F7/544

    Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to implement a neural network. An apparatus to implement a neural network, the apparatus comprising memory formed on a substrate, neural network inference logic formed on the same substrate as the memory, the neural network inference logic to load a plurality of neural network parameters in a multiply-accumulate register, and perform a sample-multiply-add operation on the neural network parameter values and input data to generate a neural network inference result, and a memory controller to transfer the neural network inference result to at least one of a host memory external to the substrate or a host processor external to the substrate.

    Use of temporal motion vectors for 3D reconstruction
    48.
    发明授权
    Use of temporal motion vectors for 3D reconstruction 有权

    公开(公告)号：US10769849B2

    公开(公告)日：2020-09-08

    申请号：US15772740

    申请日：2016-11-04

    Applicant: INTEL CORPORATION

    Inventor： Sridhar Uyyala ,  Bradley A. Jackson ,  Ignacio J. Alvarez ,  Deepak S. Vembar

    IPC: G06T17/20 ,  G06T17/00 ,  G06T7/215 ,  G06T7/55 ,  G06T7/292 ,  G06T15/00 ,  G06T15/08

    Abstract: Techniques for three-dimensional (3D) reconstruction of a dynamic scene as a set of voxels are provided. One technique includes: receiving, by a processor, image data from each of two or more spatially-separated sensors observing the scene from a corresponding two or more vantage points; fusing, by the processor, the image data into the set of voxels on a frame-by-frame basis; segmenting, by the processor, the image data into objects that constitute the scene; detecting, by the processor, which of the objects remain static from frame to frame, remaining ones of the objects being dynamic; filtering, by the processor, the set of voxels to remove those of the voxels corresponding to the static objects, to produce a dynamic subset of the voxels; and outputting, by the processor to a display device, those of the voxels corresponding to the dynamic objects (such as the dynamic subset) and not to the static objects.

    High-fidelity 3D reconstruction using facial features lookup and skeletal poses in voxel models
    49.
    发明授权
    High-fidelity 3D reconstruction using facial features lookup and skeletal poses in voxel models 有权

    公开(公告)号：US10580143B2

    公开(公告)日：2020-03-03

    申请号：US15772741

    申请日：2016-11-04

    Applicant: INTEL CORPORATION

    Inventor： Sridhar Uyyala ,  Ignacio J. Alvarez ,  Bradley A. Jackson ,  Deepak S. Vembar

    IPC: G06T7/215 ,  G06T17/10 ,  G06K9/00 ,  G06T1/20 ,  G06T13/40 ,  G06T17/20 ,  G06K9/62

    Abstract: Techniques for high-fidelity three-dimensional (3D) reconstruction of a dynamic scene as a set of voxels are provided. One technique includes: receiving, by a processor, image data from each of two or more spatially-separated sensors observing the scene from a corresponding two or more vantage points; generating, by the processor, the set of voxels from the image data on a frame-by-frame basis; reconstructing, by the processor, surfaces from the set of voxels to generate low-fidelity mesh data; identifying, by the processor, performers in the scene from the image data; obtaining, by the processor, high-fidelity mesh data corresponding to the identified performers; and merging, by the processor, the low-fidelity mesh data with the high-fidelity mesh data to generate high-fidelity 3D output. The identifying of the performers includes: segmenting, by the processor, the image data into objects; and classifying, by the processor, those of the objects representing the performers.

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