Depth features to recognise dyadic interactions

KEÇELİ A. S., KAYA A., CAN A. B.

IET Computer Vision, vol.12, no.3, pp.331-339, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 12 Issue: 3
  • Publication Date: 2018
  • Doi Number: 10.1049/iet-cvi.2017.0204
  • Journal Name: IET Computer Vision
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.331-339
  • Keywords: 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 University Affiliated: Yes