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    STEREOSCOPIC OBJECT DETECTION LEVERAGING ASSUMED DISTANCE
    1.
    发明公开
    STEREOSCOPIC OBJECT DETECTION LEVERAGING ASSUMED DISTANCE 审中-公开
    STEREOSKOPISCHE OBJEKTERKENNUNG UNTER NUTZUNG DESGESCHÄTZTENABSTANDES

    公开(公告)号：EP3014522A1

    公开(公告)日：2016-05-04

    申请号：EP14747170.0

    申请日：2014-06-23

    申请人： Microsoft Technology Licensing, LLC

    发明人： NISTER, David ,  DOLLAR, Piotr ,  KIENZLE, Wolf ,  RADOJEVIC, Mladen ,  ASHMAN, Matthew S. ,  STOJILJKOVIC, Ivan ,  VUKOSAVLJEVIC, Magdalena

    IPC分类号： G06K9/00 ,  G06F3/01 ,  G06K9/62

    摘要： A method of object detection includes receiving a first image taken by a first stereo camera, receiving a second image taken by a second stereo camera, and offsetting the first image relative to the second image by an offset distance selected such that each corresponding pixel of offset first and second images depict a same object locus if the object locus is at an assumed distance from the first and second stereo cameras. The method further includes locating a target object in the offset first and second images.

    摘要翻译： 一种物体检测方法包括：接收由第一立体摄影机拍摄的第一图像，接收由第二立体相机拍摄的第二图像，并且相对于第二图像偏移第一图像一个偏移距离，使得每个对应的偏移像素 如果对象轨迹距离第一立体相机和第二立体相机处于假定距离，则第一和第二图像描绘相同的对象轨迹。 该方法还包括在偏移的第一和第二图像中定位目标对象。

    AUTOMATIC CLASSIFICATION AND COLOR ENHANCEMENT OF A MARKABLE SURFACE
    3.
    发明公开
    AUTOMATIC CLASSIFICATION AND COLOR ENHANCEMENT OF A MARKABLE SURFACE 审中-公开
    一个表面标记的自动分类和颜色加固

    公开(公告)号：EP2932436A1

    公开(公告)日：2015-10-21

    申请号：EP13817795.1

    申请日：2013-12-13

    申请人： Microsoft Technology Licensing, LLC

    发明人： VUGDELIJA, Milan ,  VUKOSAVLJEVIC, Magdalena ,  NIJEMCEVIC, Djordje

    IPC分类号： G06K9/22 ,  G06F3/042 ,  G06K9/32 ,  G06K9/38

    CPC分类号： G06K9/46 ,  G06F3/0425 ,  G06K9/222 ,  G06K9/3241 ,  G06K9/38

    摘要： Architecture that automatically computes if a quadrangular object captured in a given image is or is not a markable board (e.g., a whiteboard, green board, chalkboard, etc.). The markable board has a surface on which marks can be applied using chalk, ink, dry ink, or any other suitable marking instrument or tool for the given surface. The imaged quadrangular object can be defined as having a background image and a foreground image. The background image is representative of a markable board with no applied surface marks and the foreground image comprises all discernible marks applied to the board surface, but does not include the background image. A set of performance- friendly features is received and processed by a machine-learning classifier to compute if the given quadrangular object is a markable board. Thereafter, if the given image is determined to be a markable board, image enhancement is performed.