Window size impact in human activity recognition.
Window size impact in human activity recognition.
复制标题
DOI：
10.3390/s140406474
复制
发表时间：
2014-04-09
期刊：
影响因子：
--
通讯作者：
Rojas I
中科院分区：
文献类型：
--
作者：
Banos O;Galvez JM;Damas M;Pomares H;Rojas I
信号分割是活动识别过程中的一个关键阶段;然而，到目前为止，这一点很少且模糊不清。窗口方法通常用于分割，但对于应优选使用哪个窗口大小没有明确的共识。事实上，大多数设计通常依赖于以前作品中使用的人物，但没有严格的研究支持它们。直观地，减小窗口大小允许更快的活动检测，以及减少的资源和能量需求。相反，大数据窗口通常被认为是识别复杂活动的依据。在这项工作中，我们提出了一个广泛的研究，以公平地描述窗口化过程，以确定其影响内的活动识别过程中，并帮助澄清一些习惯性的假设，在识别系统的设计。为此，一些最广泛使用的活动识别程序进行了评估，为广泛的窗口大小和活动。从评估来看，间隔1-2秒证明在识别速度和准确性之间提供了最佳的折衷。这项研究，特别是针对身体活动识别系统，进一步提供了一套指导方针，旨在促进系统的定义和配置，根据特定的应用要求和目标活动的设计。
Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.
登录
查看更多内容
影响因子：
--
作者：
Figo, Davide;Diniz, Pedro C.;Cardoso, Joao M. P.
通讯作者：
Cardoso, Joao M. P.
影响因子：
3.3
作者：
Arlot, Sylvain;Celisse, Alain
通讯作者：
Celisse, Alain
影响因子：
2.4
作者：
Aminian, K;Najafi, B;Robert, P
通讯作者：
Robert, P
影响因子：
3.9
作者：
Banos, Oresti;Damas, Miguel;Rojas, Ignacio
通讯作者：
Rojas, Ignacio
影响因子：
7.5
作者：
Amft, Oliver;Troester, Gerhard
通讯作者：
Troester, Gerhard