Find in Library

Human action recognition and action evaluation are hot research issues in recent years. Technologies of action recognition and action evaluation share similarities in terms of data sources, data pre-processing, feature description, etc. In conjunction with the significant recent growth of application requirements, numerous studies on action recognition and evaluation appear. However, the differences and connections between human action reco-gnition and evaluation, as well as their theoretical methods and technical routes, have not been systematically analyzed and summarized. Starting from the perspective of application purpose and technical characteristics, the relationship between the two is discussed, and a clearer concept definition is given. On this basis, action recognition and action evaluation are summarized into a unified technical framework from the perspective of data processing flow. Based on this framework, the research progress and existing problems of all important links involved in motion recognition and evaluation, including data types, pre-processing, feature description, classification methods and evaluation methods, are systematically described. Among them, in the classification method section, the current action recognition classification methods are divided into statistical model-based methods and deep learning-based methods for discussion; and in the evaluation method section, based on the intervention method of expert know-ledge, the current action evaluation related work is divided into four categories and systematically sorted out. Finally, the bottlenecks and the focus of future research are summarized and prospected.