Automatic Micro-Expression Apex Frame Spotting using Local Binary Pattern from Six Intersection Planes
Paper ID : 1024-MVIP2020 (R1)
Vida Esmaeili1, Mahmood Mohassel-Feghhi *2, Seyed-Omid Shahdi3
1Faculty of Electrical and Computer Engineering, University of Tabriz
2Faculty of Electrical and Computer Engineering University of Tabriz
3Faculty of Electrical, Biomedical and Mechatronics Qazvin Branch, Islamic Azad University
Facial expressions are one of the most effective ways for non-verbal communications, which can be expressed as the Micro-Expression (ME) in the high-stake situations. The MEs are involuntary, rapid, and, subtle, and they can reveal real human intentions. However, their feature extraction is very challenging due to their short duration and low intensity. Although Local Binary Pattern from Three Orthogonal Plane (LBP-TOP) feature extractor is useful for the ME analysis, it does not consider essential information. To address this problem, we propose a new feature extractor called Local Binary Pattern from Six Intersection Planes (LBP-SIPl). This method extracts LBP code on six intersection planes, and then it combines them. Results show that the proposed method has superior performance in apex frame spotting automatically in comparison with the relevant methods on the CASME database. Simulation results show that, using the proposed method, the apex frame has been spotted in 43% of subjects in the CASME database, automatically. Also, the mean absolute error of 1.76 is achieved, using our novel proposed method.
Apex frame spotting, local binary pattern, mean absolute error, micro expression
Status : Paper Accepted (Oral Presentation)