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    Motion tracking with multiple 3D cameras
    22.
    发明授权
    Motion tracking with multiple 3D cameras 有权

    公开(公告)号：US11354938B2

    公开(公告)日：2022-06-07

    申请号：US16763287

    申请日：2018-11-13

    Applicant: CARMEL HAIFA UNIVERSITY ECONOMIC CORPORATION LTD.

    Inventor： Ilan Shimshoni ,  Hagit Hel-Or ,  Nadav Fredi Eichler ,  Shmuel Raz

    IPC: G06K9/00 ,  G06T7/80 ,  G06T7/285 ,  G06T7/73 ,  G06K9/46 ,  G06T5/50 ,  G06V40/20 ,  G06V10/46 ,  G06V20/64

    Abstract: A system comprising at least two three-dimensional (3D) cameras that are each configured to produce a digital image with a depth value for each pixel of the digital image; and a processor configured to: perform inter-camera calibration by: (i) estimating a pose of a subject, based, at least in part, on a skeleton representation of a subject captured each of by said at least two 3D cameras, wherein said skeleton representation identifies a plurality of skeletal joints of said subject, and (ii) enhancing the estimated pose based, at least in part, on a 3D point cloud of a scene containing the subject, as captured by each of said at least two 3D cameras, and perform data merging of digital images captured by said at least two 3D cameras, wherein the data merging is per each of said identifications.

    CREATING A USER MODEL USING COMPONENT BASED APPROACH
    27.
    发明申请
    CREATING A USER MODEL USING COMPONENT BASED APPROACH 有权
    使用基于组件的方法创建用户模型

    公开(公告)号：US20130332897A1

    公开(公告)日：2013-12-12

    申请号：US13911216

    申请日：2013-06-06

    Applicant: Carmel - Haifa University Economic Corporation Ltd.

    Inventor： Eyal Dim ,  Tsvi Kuflik

    IPC: G06F9/44

    CPC classification number: G06F8/35 ,  G06F8/36

    Abstract: A computerized method of creating a user model, comprising: 1) Providing one or more software component collections containing software components. Each of the software components is associated with a single attribute and has: a. An attribute generation engine for calculating an attribute data. b. An attribute repository which stores the attribute data. c. An output object which outputs the attribute data to another of the plurality of software components. d. A metadata field which holds an identifier relating to the respective software component. 2) Selecting by a developer, a subset of software components. 3) Defining by the developer, a plurality of data links mapping data flow among the members of the subset. 4) Generating a user model based on the subset and the data links. 5) Outputting the user model.

    Abstract translation: 一种创建用户模型的计算机化方法，包括：1）提供包含软件组件的一个或多个软件组件集合。 每个软件组件都与一个属性相关联，并具有：a。 一种用于计算属性数据的属性生成引擎。 b。 存储属性数据的属性存储库。 C。 将属性数据输出到多个软件组件中的另一个的输出对象。 d。 元数据字段，其保存与各个软件组件相关的标识符。 2）由开发人员选择软件组件的子集。 3）由开发人员定义多个数据链路，用于映射子集成员之间的数据流。 4）根据子集和数据链接生成用户模型。 5）输出用户模型。

    Apparatus and method for efficient adaptation of finite element meshes for numerical solutions of partial differential equations
    28.
    发明申请
    Apparatus and method for efficient adaptation of finite element meshes for numerical solutions of partial differential equations 失效
    用于偏微分方程数值解的有限元网格有效适应的装置和方法

    公开(公告)号：US20040133616A1

    公开(公告)日：2004-07-08

    申请号：US10657210

    申请日：2003-09-09

    Applicant: Carmel - Haifa University Economic Corporation Ltd

    Inventor： Larry Manevitz ,  Akram Bitar ,  Dan Givoli

    IPC: G06F007/38

    CPC classification number: G06F17/13 ,  G06F17/5018

    Abstract: A device for calculating numerical solutions for partial differential equations in successive intervals using adaptive meshes, comprises: a neural network part for producing predictions of gradients at a following interval based on gradients available from previous intervals, and a mesh adaptation part, associated with said neural network part, configured for adapting a mesh over a domain of a respective partial differential equation using said predictions, such that said mesh adaptively refines itself about emerging regions of complexity as said partial differential equation progresses over said successive intervals. The neural network part succeeds in its predictions since its use herein is equivalent to using time series function fitting techniques.

    Abstract translation: 一种用于使用自适应网格在连续间隔中计算偏微分方程的数值解的装置，包括：神经网络部分，用于基于从先前间隔可用的梯度产生以下间隔的梯度预测，以及与所述神经元相关联的网格适应部分 网络部分，被配置为使用所述预测来适应各个偏微分方程的域上的网格，使得当所述偏微分方程在所述连续间隔上进行时，所述网格自适应地对新出现的复杂区域进行自适应细化。 神经网络部分成功地进行了预测，因为它的使用相当于使用时间序列函数拟合技术。

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