GREEDY SEARCH FOR DESCRIPTIVE SPATIAL FACE FEATURES

Creative Commons License

Gacav C., Benligiray B., Topal C.

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Louisiana, Amerika Birleşik Devletleri, 5 - 09 Mart 2017, ss.1497-1501, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icassp.2017.7952406
  • Basıldığı Şehir: Louisiana
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.1497-1501
  • Anahtar Kelimeler: facial expression recognition, spatial features, sequential forward selection
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Anadolu Üniversitesi Adresli: Evet

Özet

Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.