Harnessing Machine Learning for interpersonal physical alignment

Roi Yozevitch, Hila Gvirts, Ornit Apelboim, Elhanan Mishraky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538663783
DOIs
StatePublished - 2 Jul 2018
Event2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 - Eilat, Israel
Duration: 12 Dec 201814 Dec 2018

Publication series

Name2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018

Conference

Conference2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Country/TerritoryIsrael
CityEilat
Period12/12/1814/12/18

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