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Facial expressions are one of the most effective ways for non-verbalcommunications, which can be expressed as the Micro-Expression (ME) in thehigh-stake situations. The MEs are involuntary, rapid, and, subtle, and theycan reveal real human intentions. However, their feature extraction is verychallenging due to their low intensity and very short duration. Although LocalBinary Pattern from Three Orthogonal Plane (LBP-TOP) feature extractor isuseful for the ME analysis, it does not consider essential information. Toaddress this problem, we propose a new feature extractor called Local BinaryPattern from Six Intersection Planes (LBP-SIPl). This method extracts LBP codeon six intersection planes, and then it combines them. Results show that theproposed method has superior performance in apex frame spotting automaticallyin comparison with the relevant methods on the CASME database. Simulationresults show that, using the proposed method, the apex frame has been spottedin 43% of subjects in the CASME database, automatically. Also, the meanabsolute error of 1.76 is achieved, using our novel proposed method.

Automatic Micro-Expression Apex Frame Spotting using Local Binary Pattern from Six Intersection Planes