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    • 1. 发明申请
    • EFFICIENT GESTURE PROCESSING
    • 有效的手势处理
    • WO2012009214A2
    • 2012-01-19
    • PCT/US2011043319
    • 2011-07-08
    • INTEL CORPRAFFA GIUSEPPENACHMAN LAMALEE JINWON
    • RAFFA GIUSEPPENACHMAN LAMALEE JINWON
    • G06F3/03G06F9/44
    • G06F3/017G01C19/00G01P15/18G06F1/1694G06F3/0346H04M2250/12
    • Embodiments of the invention describe a system to efficiently execute gesture recognition algorithms. Embodiments of the invention describe a power efficient staged gesture recognition pipeline including multimodal interaction detection, context based optimized recognition, and context based optimized training and continuous learning. Embodiments of the invention further describe a system to accommodate many types of algorithms depending on the type of gesture that is needed in any particular situation. Examples of recognition algorithms include but are not limited to, HMM for complex dynamic gestures (e.g. write a number in the air), Decision Trees (DT) for static poses, peak detection for coarse shake/whack gestures or inertial methods (INS) for pitch/roll detection.
    • 本发明的实施例描述了一种有效执行手势识别算法的系统。 本发明的实施例描述了包括多模式交互检测,基于上下文的优化识别以及基于上下文的优化训练和连续学习的功率有效的分级手势识别流水线。 本发明的实施例进一步描述了一种系统,以适应取决于在任何特定情况下所需的手势类型的多种类型的算法。 识别算法的例子包括但不限于用于复杂动态手势(例如在空中写数字)的HMM,用于静态姿势的决策树(DT),用于粗糙摇晃/重击手势或惯性方法(INS)的峰值检测,用于 俯仰/滚转检测。