Citation

Buhari, Adamu Muhammad and Ooi, Chee Pun and Baskaran, Vishnu Monn and Phan, Raphaël C W and Kok, Sheik Wong and Tan, Wooi Haw (2020) FACS-Based Graph Features for Real-Time Micro-Expression Recognition. Journal of Imaging, 6 (12). p. 130. ISSN 2313-433X

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Abstract

Several studies on micro-expression recognition have contributed mainly to accuracy improvement. However, the computational complexity receives lesser attention comparatively and therefore increases the cost of micro-expression recognition for real-time application. In addition, majority of the existing approaches required at least two frames (i.e., onset and apex frames) to compute features of every sample. This paper puts forward new facial graph features based on 68-point landmarks using Facial Action Coding System (FACS). The proposed feature extraction technique (FACS-based graph features) utilizes facial landmark points to compute graph for different Action Units (AUs), where the measured distance and gradient of every segment within an AU graph is presented as feature. Moreover, the proposed technique processes ME recognition based on single input frame sample. Results indicate that the proposed FACS-baed graph features achieve up to 87.33% of recognition accuracy with F1-score of 0.87 using leave one subject out cross-validation on SAMM datasets. Besides, the proposed technique computes features at the speed of 2 ms per sample on Xeon Processor E5-2650 machine.

Item Type:	Article
Uncontrolled Keywords:	Facial expression; micro-expression; emotion recognition; real-time classification; feature extraction
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Sep 2021 23:13
Last Modified:	30 Sep 2021 23:13
URII:	http://shdl.mmu.edu.my/id/eprint/8452

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