Depth features to recognise dyadic interactions

KEÇELİ A. S., KAYA A., CAN A. B.

IET Computer Vision, cilt.12, sa.3, ss.331-339, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 3
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1049/iet-cvi.2017.0204
  • Dergi Adı: IET Computer Vision
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.331-339
  • Anahtar Kelimeler: gesture recognition, feature extraction, image sequences, image representation, support vector machines, depth feature extraction, dyadic interaction recognition, depth sensors, activity recognition, human-computer interaction, human-to-human interactions, hand-crafted features, depth frames, Relieff algorithm, interaction sequence representation, nonlinear input mapping method, random forest, K-nearest neighbour, support vector machine, SVM classifiers, joint distances, joint angles, joint spherical coordinates, composite kernel SVM
  • Hacettepe Üniversitesi Adresli: Evet