A Novel Combined Optical Flow Approach for Comprehensive Micro-Expression Recognition
This addresses a domain-specific issue for emotion analysis researchers by providing an incremental improvement in feature representation for micro-expression recognition.
The paper tackled the problem of micro-expression recognition by integrating both onset-to-apex and apex-to-offset phases in optical flow, resulting in improved performance on CASMEII and SAMM datasets.
Facial micro-expressions are brief, involuntary facial movements that reveal hidden emotions. Most Micro-Expression Recognition (MER) methods that rely on optical flow typically focus on the onset-to-apex phase, neglecting the apex-to-offset phase, which holds key temporal dynamics. This study introduces a Combined Optical Flow (COF), integrating both phases to enhance feature representation. COF provides a more comprehensive motion analysis, improving MER performance. Experimental results on CASMEII and SAMM datasets show that COF outperforms single optical flow-based methods, demonstrating its effectiveness in capturing micro-expression dynamics.