TY - GEN
T1 - Harnessing Machine Learning for interpersonal physical alignment
AU - Yozevitch, Roi
AU - Gvirts, Hila
AU - Apelboim, Ornit
AU - Mishraky, Elhanan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This work presents a novel way to determine interpersonal physical synchrony state by inspecting hands' postures obtained from a unique 3D depth camera device named Leap-Motion Controller. Several ML methods are utilized such as SVM, shallow feed-forward ANN and XGBoot. We show that even a simple ANN can outperform XgBoost in simple classification tasks.
AB - This work presents a novel way to determine interpersonal physical synchrony state by inspecting hands' postures obtained from a unique 3D depth camera device named Leap-Motion Controller. Several ML methods are utilized such as SVM, shallow feed-forward ANN and XGBoot. We show that even a simple ANN can outperform XgBoost in simple classification tasks.
UR - https://www.scopus.com/pages/publications/85063147016
U2 - 10.1109/ICSEE.2018.8646075
DO - 10.1109/ICSEE.2018.8646075
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AN - SCOPUS:85063147016
T3 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
BT - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Y2 - 12 December 2018 through 14 December 2018
ER -