@article{11127,
  keywords = {Bi-directional analysis, Convolution, Cultural heritages, Deep learning, Intangible cultural heritage, Intangible cultural heritages, Learning systems, Long short-term memory, Low-cost sensors, machine learning, Monitoring capabilities, Motion Primitives Classification, Motion analysis, Motion primitives, Processing layer, Serious Game, Serious games, Visual information, dance},
  author = {Nikolaos Bakalos and Ioannis Rallis and Nikolaos Doulamis and Anastasios Doulamis and Athanasios Voulodimos and Vassilios Vescoukis},
  title = {Motion Primitives Classification Using Deep Learning Models for Serious Game Platforms},
  abstract = {Serious games are receiving increasing attention in the field of cultural heritage (CH) applications. A special field of CH and education is intangible cultural heritage and particularly dance. Machine learning (ML) tools are necessary elements for the success of a serious game platform since they introduce intelligence in processing and analysis of users  interactivity. ML provides intelligent scoring and monitoring capabilities of the user s progress in a serious game platform. In this article, we introduce a deep learning model for motion primitive classification. The model combines a convolutional processing layer with a bidirectional analysis module. This way, RGB information is efficiently handled by the hierarchies of convolutions, while the bidirectional properties of a long short term memory (LSTM) model are retained. The resulting convolutionally enhanced bidirectional LSTM (CEBi-LSTM) architecture is less sensitive to skeleton errors, occurring using low-cost sensors, such as Kinect, while simultaneously handling the high amount of detail when using RGB visual information.},
  volume = {40},
  number = {4},
  pages = {26-38},
  issn = {02721716 (ISSN)},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084052185&doi=10.1109%2fMCG.2020.2985035&partnerID=40&md5=b5bfb5879e8524910a8ae112d1fe5daf},
  doi = {10.1109/MCG.2020.2985035},
  note = {Publisher: IEEE Computer Society},
}