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METHOD AND APPARATUS FOR DETECTING MODE OF MOTION WITH PRINCIPAL COMPONENT ANALYSIS AND HIDDEN MARKOV MODEL

机译:主成分分析和隐马尔可夫模型的运动模式检测方法及装置

摘要

A method, computer-readable storage device and apparatus for determining a mode of motion are disclosed. For example, a method receives training data comprising gait information associated with a plurality of different modes of motion. The method performs principal component analysis on the training data to extract principal components from the training data and generates a hidden markov model for each of a plurality of different modes of motion based upon the training data. The method receives testing data comprising gait information, transforms the testing data based upon the principal components and calculates a likelihood of the testing data based upon each hidden markov model for each of the plurality of different modes of motion. The method determines the mode of motion of the testing data, where the mode of motion is one of the plurality of different modes of motion for which a highest likelihood is calculated.
机译:公开了一种用于确定运动模式的方法,计算机可读存储设备和装置。例如,一种方法接收训练数据,该训练数据包括与多个不同运动模式相关联的步态信息。该方法对训练数据执行主成分分析,以从训练数据中提取主成分,并基于训练数据为多个不同运动模式中的每一个生成隐藏的马尔可夫模型。该方法接收包括步态信息的测试数据,基于主要成分对测试数据进行变换,并且基于针对多个不同运动模式中的每一个的每个隐马尔可夫模型来计算测试数据的可能性。该方法确定测试数据的运动模式,其中运动模式是针对其计算出最高似然性的多个不同运动模式之一。

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