Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods

Xiaohua Huang

355 citations0/0 files storedIEEE Transactions on Affective Computing

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Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Abstract

Micro-expressions (MEs) are rapid, involuntary facial expressions which reveal emotions that people do not intend to show. Studying MEs is valuable as recognizing them has many important applications, particularly in forensic science and psychotherapy. However, analyzing spontaneous MEs is very challenging due to their short duration and low intensity. Automatic ME analysis includes two tasks: ME spotting and ME recognition. For ME spotting, previous studies have focused on posed rather than spontaneous videos. For ME recognition, the performance of previous studies is low. To address these challenges, we make the following contributions: (i) We propose the first method for spotting spontaneous MEs in long videos (by exploiting feature difference contrast). This method is training free and works on arbitrary unseen videos. (ii) We present an advanced ME recognition framework, which outperforms previous work by a large margin on two challenging spontaneous ME databases (SMIC and CASMEII). (iii) We propose the first automatic ME analysis system (MESR), which can spot and recognize MEs from spontaneous video data. Finally, we show our method outperforms humans in the ME recognition task by a large margin, and achieves comparable performance to humans at the very challenging task of spotting and then recognizing spontaneous MEs.

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References

1997Affective Computing 2008A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions 2002Comprehensive database for facial expression analysis 1995Emotion elicitation using films 1969Nonverbal Leakage and Clues to Deception †2005Web-Based Database for Facial Expression Analysis 2014CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation 2013A Spontaneous Micro-expression Database: Inducement, collection and baseline

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2019Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition 2021Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms 2019Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-Expressions 2018Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition 2020Revealing the Invisible With Model and Data Shrinking for Composite-Database Micro-Expression Recognition

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