A review of motion analysis methods for human Nonverbal Communication Computing

被引:39
作者
Metaxas, Dimitris [1 ]
Zhang, Shaoting [1 ]
机构
[1] Rutgers State Univ, Ctr Computat Biomed Imaging & Modeling CBIM, Dept Comp Sci, Piscataway, NJ 08855 USA
基金
美国国家科学基金会;
关键词
Nonverbal Communication Computing; Motion analysis; Face tracking; Facial expression recognition; Gesture recognition; Group activity analysis; FACIAL EXPRESSION RECOGNITION; ACTIVE APPEARANCE MODELS; DENSITY PROPAGATION; DEFORMABLE MODELS; BINARY PATTERNS; EVENT DETECTION; FACE TRACKING; OPTICAL-FLOW; SHAPE; ROBUST;
D O I
10.1016/j.imavis.2013.03.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Human Nonverbal Communication Computing aims to investigate how people exploit nonverbal aspects of their communication to coordinate their activities and social relationships. Nonverbal behavior plays important roles in message production and processing, relational communication, social interaction and networks, deception and impression management, and emotional expression. This is a fundamental yet challenging research topic. To effectively analyze Nonverbal Communication Computing, motion analysis methods have been widely investigated and employed. In this paper, we introduce the concept and applications of Nonverbal Communication Computing and also review some of the motion analysis methods employed in this area. They include face tracking, expression recognition, body reconstruction, and group activity analysis. In addition, we also discuss some open problems and the future directions of this area. (C) 2013 Published by Elsevier B.V.
引用
收藏
页码:421 / 433
页数:13
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