期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2018
卷号：96
期号：14
出版社：Journal of Theoretical and Applied
摘要：Recognition of human activities is a challenging task due to human�s tendency to perform activities not only in a simple way, but also in a complex and multitasking way. Many research attempts address the recognition of simple activities, but little work targets the recognition of complex activities. Currently research on complex activity recognition using sensors is growing in many application domains. This paper provides an analysis of the most prominent complex sensor-based activity recognition. We analyze the structure and working methodology of the existing complex activities recognition systems, discuss their strengths and weaknesses. In addition, we evaluate existing proposals from three different perspectives including overall system evaluation, performance evaluation, and dataset evaluation.
关键词：Complex Human Activities Recognition; Conditional Random Field; Hidden Markov Model; Bayesian Network; Random Forest; Context Modeling; Semantic Reasoning
