Penguatan Ketepatan Pengenalan Wajah Viola-Jones Dengan Pelacakan

  • Mangaras Yanu Florestiyanto Program Studi Teknik Informatika, Universitas Pembangunan Nasional “Veteran” Yogyakarta, DI Yogyakarta
  • Awang Hendrianto Pratomo Program Studi Teknik Informatika, Universitas Pembangunan Nasional “Veteran” Yogyakarta, DI Yogyakarta
  • Nidya Indah Sari Program Studi Teknik Informatika, Universitas Pembangunan Nasional “Veteran” Yogyakarta, DI Yogyakarta
Keywords: Pengenalan Wajah, Pelacakan, Viola-Jones, Euclidean Distance

Abstract

Aplikasi pengenalan wajah sebagian besar berorientasi pada penguatan sistem keamanan dan pemantauan. Aplikasi-aplikasi tersebut banyak dikembangkan akibat adanya kajian penguatan ketepatan pengenalan wajah yang dikembangkan terus-menerus oleh peneliti. Variasi fitur wajah setiap orang yang kompleks dan perubahannya dari waktu ke waktu, bahkan dalam waktu yang singkat menjadikan optimalisasi ketepatan pengenalannya semakin rumit. Studi ini bertujuan untuk meningkatkan performa metode Viola-Jones pada target yang bergerak dengan integrasi algoritma tracking. Algoritma tracking yang diintegrasikan adalah algoritma Continuously Adaptive Mean Shift (Camshift). Algoritma ini merupakan pengembangan dari algoritma Mean Shift yang secara terus menerus melakukan adaptasi atau penyesuaian terhadap distribusi probabilitas warna yang selalu berubah tiap pergantian frame dari sebuah sequence video. Integrasi tracking dengan Viola-Jones signifikan meningkatkan ketepatan pengenalan wajah dibandingkan tanpa tracking yaitu sebesar 96%.

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Published
2020-07-13
Section
Articles