Gomes Diana, Moreira Dinis, Costa João, Graça Ricardo, Madureira João
Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal.
Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.
Sensors (Basel). 2019 Jul 17;19(14):3138. doi: 10.3390/s19143138.
The increasing popularity of water sports-surfing, in particular-has been raising attention to its yet immature technology market. While several available solutions aim to characterise surf session events, this can still be considered an open issue, due to the low performance, unavailability, obtrusiveness and/or lack of validation of existing systems. In this work, we propose a novel method for wave, paddle, sprint paddle, dive, lay, and sit events detection in the context of a surf session, which enables its entire profiling with 88.1% accuracy for the combined detection of all events. In particular, waves, the most important surf event, were detected with second precision with an accuracy of 90.3%. When measuring the number of missed and misdetected wave events, out of the entire universe of 327 annotated waves, wave detection performance achieved 97.5% precision and 94.2% recall. These findings verify the precision, validity and thoroughness of the proposed solution in constituting a complete surf session profiling system, suitable for real-time implementation and with market potential.
水上运动，尤其是冲浪运动日益普及，这使得人们开始关注其尚不成熟的技术市场。尽管有几种现有的解决方案旨在对冲浪活动进行特征描述，但由于现有系统性能低下、无法使用、干扰性强和/或缺乏验证，这一问题仍可被视为一个开放性问题。在这项工作中，我们提出了一种在冲浪活动中检测波浪、划水、冲刺划水、潜水、躺姿和坐姿事件的新方法，该方法能够以88.1%的准确率对所有事件进行联合检测，从而实现对冲浪活动的全面剖析。特别是，最重要的冲浪事件——波浪，检测精度位居第二，准确率为90.3%。在测量漏检和误检的波浪事件数量时，在327个标注波浪的整个范围内，波浪检测性能达到了97.5%的精度和94.2%的召回率。这些发现验证了所提出的解决方案在构建一个完整的冲浪活动剖析系统方面的精确性、有效性和全面性，该系统适用于实时实施且具有市场潜力。
