Real-Time Gesture Recognition Using 3D Sensory Data and a Light Convolutional Neural Network
Author:
Affiliation:
1. University of Alabama in Huntsville, Huntsville, AL, USA
2. Rochester Institute of Technology, Rochester, NY, USA
3. Army Research Lab, Huntsville, AL, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3343031.3350958
Reference42 articles.
1. Quaternion-Based Gesture Recognition Using Wireless Wearable Motion Capture Sensors
2. Allan Pease Barbara Pease. 2006. The Definitive Book of Body Language: The Hidden Meaning Behind People's Gestures and Expressions. BANTAM DELL. https://www.ebook.de/de/product/5169074/barbara_pease_allan_pease_the_ definitive_book_of_body_language_the_hidden_meaning_behind_people_s_ gestures_and_expressions.html Allan Pease Barbara Pease. 2006. The Definitive Book of Body Language: The Hidden Meaning Behind People's Gestures and Expressions. BANTAM DELL. https://www.ebook.de/de/product/5169074/barbara_pease_allan_pease_the_ definitive_book_of_body_language_the_hidden_meaning_behind_people_s_ gestures_and_expressions.html
3. J. C. Calella F. R. Ortega N. Rishe J. F. Bernal and A. Barreto. 2016. HandMagic: Towards user interaction with inertial measuring units. In 2016 IEEE SENSORS. 1--3. https://doi.org/10.1109/ICSENS.2016.7808524 J. C. Calella F. R. Ortega N. Rishe J. F. Bernal and A. Barreto. 2016. HandMagic: Towards user interaction with inertial measuring units. In 2016 IEEE SENSORS. 1--3. https://doi.org/10.1109/ICSENS.2016.7808524
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