Activity Recognition from Binary Data

R. Auber, M. Pouliquen, E. Pigeon, P. Chapon, S. Moussay
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引用次数: 5

Abstract

In this paper, an algorithm for the activity recognition from binarized accelerometric data is presented. The particularity of the proposed algorithm is the use of binary data, this constraint on data is justified by the fact that using binary data allows to save battery and memory on the connected device. The objective of the present study is to show that it is possible to perform activity recognition from these binary data. The proposed algorithm uses Auto Regressive (AR) modeling and classification using Support Vector Machine (SVM). Some results on a real-data experiment is presented for the recognition of three activity.
基于二进制数据的活动识别
本文提出了一种基于二值化加速度数据的运动识别算法。该算法的特殊之处在于使用二进制数据,这种对数据的约束是合理的,因为使用二进制数据可以节省所连接设备的电池和内存。本研究的目的是证明从这些二进制数据中进行活动识别是可能的。该算法采用自回归(AR)建模和支持向量机(SVM)分类。在实际数据实验中给出了三种活动识别的一些结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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