Preprocessing and Feature Descriptors for Facial Micro-Expression Recognition

Facial micro-expressions reveal crucial insights into human emotions, even when individuals attempt to conceal their feelings. Historically, limited research has been conducted on detecting and recognizing micro-expressions using computer vision techniques. This implementation processes spontaneous micro-expression databases through preprocessing and Haar feature-based image cropping, followed by feature extraction using Local Binary Patterns on Three Orthogonal Planes (LBP-TOP) and Local Gray-Coding Patterns on Three Orthogonal Planes (LGCP-TOP) descriptors. The system employs Support Vector Machines (SVM) for detection and classification, achieving accuracy comparable to existing state-of-the-art methods.