APPARATUS AND METHOD FOR CONTROLLING INTERFACE
    21.
    发明申请
    APPARATUS AND METHOD FOR CONTROLLING INTERFACE 审中-公开
    用于控制界面的装置和方法

    公开(公告)号:US20150370337A1

    公开(公告)日:2015-12-24

    申请号:US14842448

    申请日:2015-09-01

    Abstract: In an apparatus and method for controlling an interface, a user interface (UI) may be controlled using information on a hand motion and a gaze of a user without separate tools such as a mouse and a keyboard. That is, the UI control method provides more intuitive, immersive, and united control of the UI. Since a region of interest (ROI) sensing the hand motion of the user is calculated using a UI object that is controlled based on the hand motion within the ROI, the user may control the UI object in the same method and feel regardless of a distance from the user to a sensor. In addition, since positions and directions of view points are adjusted based on a position and direction of the gaze, a binocular 2D/3D image based on motion parallax may be provided.

    Abstract translation: 在用于控制界面的装置和方法中,用户界面(UI)可以使用没有诸如鼠标和键盘的单独工具的关于手动和用户目标的信息进行控制。 也就是说,UI控制方法提供了对UI的更直观,身临其境和统一的控制。 由于感兴趣的感兴趣区域(ROI)是使用基于ROI内的手运动来控制的UI对象来计算的,所以用户可以以相同的方法控制UI对象,而不管距离如何 从用户到传感器。 此外,由于基于目标的位置和方向来调整视点的位置和方向,可以提供基于运动视差的双目2D / 3D图像。

    APPARATUS AND METHOD FOR RECOGNIZING OBJECT USING DEPTH IMAGE
    23.
    发明申请
    APPARATUS AND METHOD FOR RECOGNIZING OBJECT USING DEPTH IMAGE 有权
    用于识别使用深度图像的对象的装置和方法

    公开(公告)号:US20140233848A1

    公开(公告)日:2014-08-21

    申请号:US14074247

    申请日:2013-11-07

    Abstract: An apparatus recognizes an object using a hole in a depth image. An apparatus may include a foreground extractor to extract a foreground from the depth image, a hole determiner to determine whether a hole is present in the depth image, based on the foreground and a color image, a feature vector generator to generate a feature vector, by generating a plurality of features corresponding to the object based on the foreground and the hole, and an object recognizer to recognize the object, based on the generated feature vector and at least one reference feature vector.

    Abstract translation: 设备使用深度图像中的孔识别对象。 装置可以包括从深度图像提取前景的前景提取器,基于前景和彩色图像确定深度图像中是否存在孔的孔确定器,用于生成特征向量的特征向量生成器, 通过基于所述前景和所述孔生成对应于所述对象的多个特征,以及基于所生成的特征向量和至少一个参考特征向量来识别所述对象的对象识别器。

    SYSTEM AND METHOD FOR LEARNING POSE CLASSIFIER BASED ON DISTRIBUTED LEARNING ARCHITECTURE
    25.
    发明申请
    SYSTEM AND METHOD FOR LEARNING POSE CLASSIFIER BASED ON DISTRIBUTED LEARNING ARCHITECTURE 审中-公开
    基于分布式学习架构学习分类器的系统与方法

    公开(公告)号:US20130185233A1

    公开(公告)日:2013-07-18

    申请号:US13740597

    申请日:2013-01-14

    CPC classification number: G06N20/00

    Abstract: A system and method for learning a pose classifier based on a distributed learning architecture. A pose classifier learning system may include an input unit to receive an input of a plurality of pieces of learning data, and a plurality of pose classifier learning devices to receive an input of a plurality of learning data sets including the plurality of pieces of learning data, and to learn each pose classifier. The pose classifier learning devices may share learning information in each stage, using a distributed/parallel framework.

    Abstract translation: 一种基于分布式学习架构学习姿态分类器的系统和方法。 姿态分类器学习系统可以包括用于接收多条学习数据的输入的输入单元和多个姿态分类器学习装置,用于接收包括多条学习数据的多个学习数据集的输入 ,并学习每个姿态分类器。 姿态分类器学习装置可以使用分布式/并行框架在每个阶段共享学习信息。

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