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, Scopus)

• 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