Research on micro-expression recognition technology based on YOLOv5
To solve the problems of small data sets,weak generalization ability and higher requirements for equipment and GPU of micro-expression recognition system,three mainstream data sets are fused and screened,and a multi-source expression data set was reconstructed.The problem of poor generalization a-bility was solved by incorporating some macro-expressions into the micro-expression data set.By training and testing based on YOLOv5 model,a relatively portable micro-expression recognition system is ob-tained.The results show that the model generalization ability is improved after the improved data set train-ing.The recognition accuracy of the trained model on the Z-MES micro-expression data set is 79.4%,which is better than before the improvement.
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