Recognition of Human daily activities

Krasimir Tonchev, Strahil Sokolov, Yuliyan Velchev, Georgi R. Balabanov, V. Poulkov
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引用次数: 7

Abstract

Capturing the type of physical activity a person is performing thorough his daily life, can inspire the development of new and innovative applications. Examples include monitoring patients' health and physical activity performance, reasoning upon the observed activity to recommend better training strategy, new therapeutic programs, etc. In this work we propose an algorithm for Human Activity Recognition based on the application of a geometrically motivated feature selection method. We test the algorithm on a standard data set and validate its performance by comparing it with the existing results of other known algorithms.
人类日常活动的识别
捕捉一个人在日常生活中进行的身体活动类型,可以激发新的创新应用的发展。例如,监测患者的健康状况和身体活动表现,根据观察到的活动进行推理,以推荐更好的训练策略,新的治疗方案等。在这项工作中,我们提出了一种基于几何动机特征选择方法的人类活动识别算法。我们在标准数据集上测试了该算法,并通过将其与其他已知算法的现有结果进行比较来验证其性能。
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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