论文标题
人类活动识别中的个性化
Personalization in Human Activity Recognition
论文作者
论文摘要
近年来，人们对能够自动识别人们进行的活动的技术越来越兴趣。该领域被称为人类活动识别（HAR）。 HAR对于监测人民的福祉至关重要，对老年人和受退行性条件影响的人的特殊考虑。主要挑战之一是由于身体特征和生活方式，人口的多样性以及如何以不同的方式进行相同的活动。在本文中，我们探讨了利用身体特征和信号相似性的可能性，以相对于不依赖此信息的深度学习分类器获得更好的结果。
In the recent years there has been a growing interest in techniques able to automatically recognize activities performed by people. This field is known as Human Activity recognition (HAR). HAR can be crucial in monitoring the wellbeing of the people, with special regard to the elder population and those people affected by degenerative conditions. One of the main challenges concerns the diversity of the population and how the same activities can be performed in different ways due to physical characteristics and life-style. In this paper we explore the possibility of exploiting physical characteristics and signal similarity to achieve better results with respect to deep learning classifiers that do not rely on this information.
