@inproceedings{3247,
  keywords = {Folk dance, Folk dances, Intangible cultural heritage, Intangible cultural heritages, Kinect sensor, Kinect sensors, Pattern recognition, Posture analysis, Posture identification, Soft computing},
  author = {Eftychios Protopapadakis and Athanasios Voulodimos and Anastasios Doulamis and Stephanos Camarinopoulos and Assoc Machinery},
  title = {A Study on the Use of Kinect Sensor in Traditional Folk Dances Recognition via Posture Analysis},
  abstract = {In this paper, we evaluate the performance of widely applied soft computing classifiers, in folk dance recognition problems, emphasizing on posture identification. In particular, the goal is to identify postures which are characteristic for the dance performed, based on exploiting simultaneously the information of 24 body joints, acquired by a Kinect II sensor. The data sets described 6 folk dances, and their variations, originating from Greece.},
  year = {2017},
  booktitle = {ACM Int. Conf. Proc. Ser.},
  volume = {Part F128530},
  pages = {305-310},
  publisher = {Association for Computing Machinery},
  school = {Association for Computing Machinery},
  isbn = {9781450352277 (ISBN)},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025118340&doi=10.1145%2f3056540.3076200&partnerID=40&md5=18dd0698978acf62a18ad43eab81494a},
  doi = {10.1145/3056540.3076200},
  note = {Journal Abbreviation: ACM Int. Conf. Proc. Ser.},
  language = {English},
}