Abstract
Micro-expressions are facial expressions that have a short duration (generally less than 0.5 s), involuntary appearance and low intensity of movement. They are regarded as unique cues revealing the hidden emotions of an individual. Although methods for the spotting and recognition of general facial expressions have been investigated, little progress has been made in the automatic spotting and recognition of micro-expressions. In this paper, we proposed the Main Directional Maximal Difference (MDMD) analysis for micro-expression spotting. MDMD uses the magnitude of maximal difference in the main direction of optical flow as a feature to spot facial movements, including micro-expressions. Based on block-structured facial regions, MDMD obtains more accurate features of the movement of expressions for automatically spotting micro-expressions and macro-expressions from videos. This method obtains both the temporal and spatial locations of facial movements. The evaluation was performed on two spontaneous databases (CAS(ME)\(^{2}\) and CASME) containing micro-expressions and macro-expressions.
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- 1.
For convenience, \((u^{HC}, v^{HC})\) means the displacement of any point.
- 2.
28 videos were removed because of relatively large movements of the head.
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Acknowledgments
This work was supported by grants from the National Natural Science Foundation of China (61379095, 61375009), and the Beijing Natural Science Foundation (4152055).
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Wang, SJ., Wu, S., Fu, X. (2017). A Main Directional Maximal Difference Analysis for Spotting Micro-expressions. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_33
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