Dong, R., Chen, Y., Cai, D., Nakagawa, S., Higaki, T., & Asai, N. Robot motion design using bunraku emotional expressions–focusing on Jo-Ha-Kyū in sounds and movements*. 34, 299-312. https://doi.org/10.1080/01691864.2019.1703811
R. Dong Y. Chen D. Cai S. Nakagawa T. Higaki N. AsaiBunraku puppet Deep learning Emotional expressions Express emotions Intangible cultural heritages Jo-Ha-Kyū Learning methods Machine design Motion analysis Motion design Robot motion Robots Uncanny valley Deep learning motion design
Bakalos, N., Rallis, I., Doulamis, N., Doulamis, A., Voulodimos, A., & Vescoukis, V. Motion Primitives Classification Using Deep Learning Models for Serious Game Platforms. 40, 26-38. https://doi.org/10.1109/MCG.2020.2985035
Nikolaos Bakalos Ioannis Rallis Nikolaos Doulamis Anastasios Doulamis Athanasios Voulodimos Vassilios VescoukisBi-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
Chen, S. -X., Li, J. -W., & Lin, J. -D. (2015). Automatic segmentation of motion capture data of Quan-Zhou chest-clapping dance. 581-585. CRC Press/Balkema. https://doi.org/10.1201/b18737-121
S.-X. Chen J.-W. Li J.-D. LinAutomatic segmentation Automatic segmentation techniques Automatic segmentations Dimensionality reduction Engineering Geometric feature Industrial engineering Intangible cultural heritages Motion analysis Motion capture Motion capture data Quan-Zhou chest-clapping dance