Abstract

Nonverbal communication is an indispensable and omnipresent element of human behaviors which includes various ways such as human action, hand gesture, and facial expression, etc. As a basic means to express a person's attitudes, feelings, and emotions, it is essential in human's communication, and also play an important role in the multimodal interactions between human and computer system. Due to the richness, flexibility, and ambiguity existing in human's nonverbal expressions, as well as being affected by personalized behavior habits, the understanding and recognition of above human's expressions involves complex intelligent technologies such as visual analysis and situational awareness based on machine learning. This paper aims to provide a systematic summary and analysis of machine learning methods and technologies in human-computer nonverbal communication. It starts with the evolution of nonverbal communication research, goes on to present the definition and classification of nonverbal communication, proceeds to review and analyze the machine learning techniques which are frequently employed in human-computer nonverbal communication, and finally expounds the development of smart learning based on neural mechanism.

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