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    • 57. 发明申请
    • SYSTEM AND METHOD FOR GENERATING A USER INTERFACE FOR TEXT AND ITEM SELECTION
    • 用于生成文本和项目选择的用户界面的系统和方法
    • US20160041729A1
    • 2016-02-11
    • US14887161
    • 2015-10-19
    • OpenTV, Inc.
    • Nicholas Daniel Doerring
    • G06F3/0484G06F3/0482
    • G06F3/04842G06F3/0236G06F3/0482G06F3/04845G06F2203/04806
    • A system and method for generating a user interface for text and item selection is disclosed. As described for various embodiments, a system and process is disclosed for providing an arrangement of selectable items, a mechanism for selection from the arrangement of selectable items, and a mechanism for adjusting the granularity of control of the selector. In one embodiment, the granularity control can be a zooming mechanism to modify the size and/or position of items in a selection set. In another embodiment, the granularity control can be a modification of the motion vector based on a distance from a reference point and the speed or quantity of deflection of a pointing device. Thus, as a selection point approaches the selection set, the motion of the selection point becomes less responsive to movement of the pointing device, so the user has more control over the positioning of the selection point relative to an item in the selection set.
    • 公开了一种用于生成用于文本和项目选择的用户界面的系统和方法。 如针对各种实施例所述,公开了用于提供可选项目的布置的系统和过程,用于从可选项目的布置中进行选择的机构以及用于调整选择器的控制粒度的机构。 在一个实施例中,粒度控制可以是缩放机制来修改选择集中的项目的大小和/或位置。 在另一个实施例中,粒度控制可以是基于与参考点的距离和指向设备的偏转速度或数量的运动矢量的修改。 因此,当选择点接近选择集合时,选择点的运动变得对指示设备的移动不那么敏感,因此用户对选择点相对于选择集合中的项目的定位具有更多的控制。
    • 59. 发明申请
    • DEVICE LOCALIZATION BASED ON A LEARNING MODEL
    • 基于学习模型的设备本地化
    • US20150371139A1
    • 2015-12-24
    • US14311077
    • 2014-06-20
    • OpenTV, Inc.
    • Ari Ranjit Kamlani
    • G06N5/04G06N99/00H04W4/02
    • H04W4/029G06N3/02H04W4/023
    • Methods and systems of localizing a device are presented. In an example method, a communication signal from a device is received by a wireless reference point during a period of time. A sequence of values is generated from the communication signal, as received by the wireless reference point, during the period of time. The sequence of values is supplied to a learning model configured to generate an output based on past values of the sequence of values and at least one predicted future value of the sequence of values. The current location of the device is estimated during the period of time based on the output of the learning model.
    • 介绍了本地化设备的方法和系统。 在示例性方法中,来自设备的通信信号在一段时间期间被无线参考点接收。 在一段时间内,从无线参考点接收的通信信号产生一系列值。 值序列被提供给学习模型,该学习模型被配置为基于值序列的过去值和值序列的至少一个预测的未来值生成输出。 根据学习模型的输出,估计设备的当前位置在一段时间内。