Pengenalan Ekspresi Mikro Wajah Berdasarkan Point Feature Tracking Menggunakan Fase Apex Pada Database Ekspresi Mikro
Abstract
Ekspresi mikro merupakan ekspresi wajah yang terjadi secara tidak disengaja untuk menyembunyikan perasaan sebenarnya (emotional leakage). Penelitian sebelumnya menggunakan seluruh area wajah dan seluruh frame pada dataset video, hal ini menghasilkan waktu komputasi tergolong lama dan terjadinya redundancy data. Kontribusi utama penelitian ini menerapkan analisa pengenalan ekspresi mikro menggunakan perbandingan frame apex dengan pilihan manual (handcrafted) dan secara acak (random sampling) dan menerapkan pelacakan titik fitur pada area alis mata dan sudut bibir. Discriminative Response Map Fitting (DRMF) sebagai metode yang membentuk titik fitur dan selanjutnya dilakukan pelacakan titik-titik fitur wajah dengan Kanade-Lucas-Tomasi (KLT). Hasil pelacakan titik-titik fitur tersebut menghasilkan data motion features sebagai data ekstraksi fitur dan dilakukan analisa perbandingan metode klasifikasi menggunakan Support Vector Machine (SVM) dan MLP-Backpropagation menggunakan dataset CASME II. Hasil eksperimen penelitian ini menunjukkan hasil yang signifikan dengan akurasi sebesar 81,3% pada MLP-Backpropagation dan waktu komputasi rata-rata 1,45 detik pada setiap video. Hal ini menunjukkan bahwa informasi pada fase apex memberikan informasi yang penting untuk pengenalan ekspresi mikro pada wajah.
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