Label distribution expression recognition algorithm based on asymptotic truth value  

渐近真值的标签分布表情识别算法

作　　者：HUANG Hao GE Hongwei 黄浩;葛洪伟(江南大学江苏省模式识别与计算智能实验室,江苏无锡214122;江南大学人工智能与计算机学院,江苏无锡214122)

机构地区：[1]School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China [2]Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Wuxi 214122, China

出　　处：《Journal of Measurement Science and Instrumentation》2021年第3期295-303,共9页测试科学与仪器（英文版）

基　　金：National Youth Natural Science Foundation of China(No.61806006);Innovation Program for Graduate of Jiangsu Province(No.KYLX160-781);Project Supported by Jiangsu University Superior Discipline Construction Project。

摘　　要：Ambiguous expression is a common phenomenon in facial expression recognition(FER).Because of the existence of ambiguous expression,the effect of FER is severely limited.The reason maybe that the single label of the data cannot effectively describe complex emotional intentions which are vital in FER.Label distribution learning contains more information and is a possible way to solve this problem.To apply label distribution learning on FER,a label distribution expression recognition algorithm based on asymptotic truth value is proposed.Under the premise of not incorporating extraneous quantitative information,the original information of database is fully used to complete the generation and utilization of label distribution.Firstly,in training part,single label learning is used to collect the mean value of the overall distribution of data.Then,the true value of data label is approached gradually on the granularity of data batch.Finally,the whole network model is retrained using the generated label distribution data.Experimental results show that this method can improve the accuracy of the network model obviously,and has certain competitiveness compared with the advanced algorithms.

关 键 词：facial expression recognition(FER) label distributed learning label smoothing ambiguous expression 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]