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    • 5. 发明申请
    • MOTION PATTERN CLASSIFICATION AND GESTURE RECOGNITION
    • 运动图案分类和姿态识别
    • US20120306745A1
    • 2012-12-06
    • US13153374
    • 2011-06-03
    • CHRISTOPHER MOOREXiaoyuan TuWilliam Matthew Vieta
    • CHRISTOPHER MOOREXiaoyuan TuWilliam Matthew Vieta
    • G06F3/033
    • G06F3/017G06F3/04842G06F3/04883G06K9/00355
    • Methods, program products, and systems for gesture classification and recognition are disclosed. In general, in one aspect, a system can determine multiple motion patterns for a same user action (e.g., picking up a mobile device from a table) from empirical training data. The system can collect the training data from one or more mobile devices. The training data can include multiple series of motion sensor readings for a specified gesture. Each series of motion sensor readings can correspond to a particular way a user performs the gesture. Using clustering techniques, the system can extract one or more motion patterns from the training data. The system can send the motion patterns to mobile devices as prototypes for gesture recognition.
    • 公开了用于手势分类和识别的方法,程序产品和系统。 通常,在一个方面,系统可以根据经验训练数据确定用于相同用户动作(例如,从表中拾取移动设备)的多个运动模式。 系统可以从一个或多个移动设备收集训练数据。 训练数据可以包括用于指定手势的多个运动传感器读数。 每个系列的运动传感器读数可以对应于用户执行手势的特定方式。 使用聚类技术,系统可以从训练数据中提取一个或多个运动模式。 系统可以将运动模式发送到移动设备作为用于手势识别的原型。
    • 8. 发明授权
    • Motion pattern classification and gesture recognition
    • 运动模式分类和手势识别
    • US09110510B2
    • 2015-08-18
    • US13153374
    • 2011-06-03
    • Christopher MooreXiaoyuan TuWilliam Matthew Vieta
    • Christopher MooreXiaoyuan TuWilliam Matthew Vieta
    • G09G5/00G06F3/01G06K9/00
    • G06F3/017G06F3/04842G06F3/04883G06K9/00355
    • Methods, program products, and systems for gesture classification and recognition are disclosed. In general, in one aspect, a system can determine multiple motion patterns for a same user action (e.g., picking up a mobile device from a table) from empirical training data. The system can collect the training data from one or more mobile devices. The training data can include multiple series of motion sensor readings for a specified gesture. Each series of motion sensor readings can correspond to a particular way a user performs the gesture. Using clustering techniques, the system can extract one or more motion patterns from the training data. The system can send the motion patterns to mobile devices as prototypes for gesture recognition.
    • 公开了用于手势分类和识别的方法,程序产品和系统。 通常,在一个方面,系统可以根据经验训练数据确定用于相同用户动作(例如,从表中拾取移动设备)的多个运动模式。 该系统可以从一个或多个移动设备收集训练数据。 训练数据可以包括用于指定手势的多个运动传感器读数。 每个系列的运动传感器读数可以对应于用户执行手势的特定方式。 使用聚类技术,系统可以从训练数据中提取一个或多个运动模式。 系统可以将运动模式发送到移动设备作为用于手势识别的原型。
    • 10. 发明授权
    • Negative pixel compensation
    • 负像素补偿
    • US08581879B2
    • 2013-11-12
    • US12691328
    • 2010-01-21
    • William Matthew Vieta
    • William Matthew Vieta
    • G06F3/045G06F3/041G06F3/044G08C21/00
    • G06F3/0418G06F3/0412G06F3/044G06F2203/04104
    • Negative pixel compensation in a touch sensor panel is disclosed. A method can compensate for a negative pixel effect in touch signal outputs due to poor grounding of an object touching the panel. To do so, the method can include determining at least one bound for a negative pixel compensation factor based on touch signal values, estimating the compensation factor within the determined bound based on the touch signal values that are negative, where the negative values indicate the presence of the negative pixel effect, and applying the estimated compensation factor to the touch signal outputs to compensate the touch signal values for the negative pixel effect.
    • 公开了触摸传感器面板中的负像素补偿。 由于接触面板的物体接地不良,一种方法可以补偿触摸信号输出中的负像素效应。 为了这样做,该方法可以包括基于触摸信号值来确定负像素补偿因子的至少一个界限,基于负的触摸信号值估计所确定的界限内的补偿因子,其中负值表示存在 并且将估计的补偿因子应用于触摸信号输出以补偿负像素效应的触摸信号值。