Gestural Interactions of Embodied Educational Technology Using One-Shot Machine Learning

Michael J. Junokas, Greg Kohlburn, Benjamin Lane, Sahil Kumar, Wai Tat Fu, Robb Lindgren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Educational research has demonstrated the importanceof embodiment in designing student learning environments,connecting bodily actions to critical concepts. Gesturalrecognition algorithms have become important in leveragingthis connection but have focused primarily on traditionallytrained machine-learning paradigms.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages1
ISBN (Electronic)9781509040230
DOIs
StatePublished - Jun 28 2017
Event12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - Washington, United States
Duration: May 30 2017Jun 3 2017

Publication series

NameProceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017

Other

Other12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017
CountryUnited States
CityWashington
Period5/30/176/3/17

ASJC Scopus subject areas

  • Media Technology
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Gestural Interactions of Embodied Educational Technology Using One-Shot Machine Learning'. Together they form a unique fingerprint.

  • Cite this

    Junokas, M. J., Kohlburn, G., Lane, B., Kumar, S., Fu, W. T., & Lindgren, R. (2017). Gestural Interactions of Embodied Educational Technology Using One-Shot Machine Learning. In Proceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017 [7961855] (Proceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FG.2017.152