Three dimensional object pose estimation which employs dense depth information
    1.
    发明授权
    Three dimensional object pose estimation which employs dense depth information 有权
    采用密集深度信息的三维物体姿态估计

    公开(公告)号:US07158656B2

    公开(公告)日:2007-01-02

    申请号:US11195039

    申请日:2005-08-01

    IPC分类号: G06K9/00

    摘要: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

    摘要翻译: 采用实时速率获得的浓度范围数据来估计关节数字的姿态。 在一种方法中,范围数据与连接补丁的模型结合使用。 每个贴片是两个圆的平面凸包,并且执行递归过程以确定与范围数据最密切相关的姿势的估计。 在本发明的另一方面,密集范围数据与图像强度信息结合使用以改善姿态跟踪性能。 范围信息用于确定对象的形状,而不是假设通用模型或从运动估计结构。 在本发明的这个方面,采用与经典亮度变化约束方程相对应的深度约束方程。 两个约束都用于共同解决运动估计。

    Three dimensional object pose estimation which employs dense depth information
    2.
    发明授权
    Three dimensional object pose estimation which employs dense depth information 有权
    采用密集深度信息的三维物体姿态估计

    公开(公告)号:US07003134B1

    公开(公告)日:2006-02-21

    申请号:US09520964

    申请日:2000-03-08

    IPC分类号: G06K9/00

    摘要: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

    摘要翻译: 采用实时速率获得的浓度范围数据来估计关节数字的姿态。 在一种方法中,范围数据与连接补丁的模型结合使用。 每个贴片是两个圆的平面凸包,并且执行递归过程以确定与范围数据最密切相关的姿势的估计。 在本发明的另一方面,密集范围数据与图像强度信息结合使用以改善姿态跟踪性能。 范围信息用于确定对象的形状,而不是假设通用模型或从运动估计结构。 在本发明的这个方面,采用与经典亮度变化约束方程相对应的深度约束方程。 两个约束都用于共同解决运动估计。

    Photo-based mobile deixis system and related techniques
    4.
    发明授权
    Photo-based mobile deixis system and related techniques 有权
    基于照片的移动指示系统及相关技术

    公开(公告)号:US07872669B2

    公开(公告)日:2011-01-18

    申请号:US10762941

    申请日:2004-01-22

    IPC分类号: H04N5/225

    CPC分类号: G06F17/30277 G06F17/30864

    摘要: A mobile deixis device includes a camera to capture an image and a wireless handheld device, coupled to the camera and to a wireless network, to communicate the image with existing databases to find similar images. The mobile deixis device further includes a processor, coupled to the device, to process found database records related to similar images and a display to view found database records that include web pages including images. With such an arrangement, users can specify a location of interest by simply pointing a camera-equipped cellular phone at the object of interest and by searching an image database or relevant web resources, users can quickly identify good matches from several close ones to find an object of interest.

    摘要翻译: 移动指示设备包括用于捕获图像的相机和耦合到相机和无线网络的无线手持设备,以将图像与现有数据库通信以找到相似的图像。 移动指示设备还包括耦合到该设备的处理器,以处理与类似图像相关的发现的数据库记录和显示器,以查看包括包括图像的网页的发现的数据库记录。 通过这样的布置,用户可以通过简单地将配备有相机的蜂窝电话指向感兴趣的对象并且通过搜索图像数据库或相关网络资源来指定感兴趣的位置,用户可以快速地从几个密切的识别符中找到良好的匹配,以找到 感兴趣的对象