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首页> 外文会议>ICA3PP 2014 >A Smartphone Location Independent Activity Recognition Method Based on the Angle Feature
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A Smartphone Location Independent Activity Recognition Method Based on the Angle Feature

机译：基于角度特征的智能手机定位独立活动识别方法

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The smartphone-based human activity recognition method is helpful in the context awareness, health monitoring and inertial positioning. Comparing with the traditional wearable computing which fixes accelerometers on the specific positions of a user body, the activity recognition method based on a smartphone faces the problem of varying sensor locations. In this paper, we lay emphasis on the study of a feature extraction algorithm which is independent of the phone locations. First, the angle motion model is presented to illustrate the human activities. The model describes the difference among walking, going upstairs and going downstairs. Then, an angle feature extraction algorithm is proposed according to the angle motion model. Our analysis shows that different activities have significantly different angle features. Finally, our experiments are introduced. The experiments include data collecting, analysis of experiments results. The experiments results show that the recognition accuracy improved by 2% through adding the angle feature to original features.
机译：基于智能手机的人类活动识别方法有助于上下文意识，健康监测和惯性定位。与传统的可穿戴计算进行比较，该可穿戴计算将加速度计固定在用户主体的特定位置，基于智能手机的活动识别方法面临不同传感器位置的问题。在本文中，我们重点研究了一种独立于电话位置的特征提取算法的研究。首先，提出了角度运动模型以说明人类活动。该模型描述了行走，楼上和楼下的差异。然后，根据角度运动模型提出了一种角度特征提取算法。我们的分析表明，不同的活动具有显着不同的角度特征。最后，介绍了我们的实验。实验包括数据收集，实验结果分析。实验结果表明，通过将角度特征添加到原始特征，识别准确性提高了2％。

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