TY - GEN
T1 - Demonstrating HighFiveLive
T2 - 14th IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
AU - Bandy, Jack
AU - Knighten, Jonathan
AU - Payton, Jamie
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/19
Y1 - 2016/4/19
N2 - Gestures are an important part of our social fabric, aiding our speech (and sometimes standing in for it) in face-to-face communications. In this demonstration, we present HighFiveLive, a smartwatch application that uses data from an onboard accelerometer to detect and classify fine-grained symbolic gestures, which convey semantic meaning and have social significance. We apply logistic regression to learn a representative model of 9 symbolic gestures as performed by 32 users; in an offline evaluation study, the model accurately classifies 92% of recognized gestures. Building on this work, we deploy the learned model in our HighFiveLive mobile application, which detects and classifies symbolic gestures in real-time as they are performed. HighFiveLive is implemented as an Android application with connection to a wrist-worn accelerometer stream (such as a Microsoft Band) as well as a standalone Apple Watch application.
AB - Gestures are an important part of our social fabric, aiding our speech (and sometimes standing in for it) in face-to-face communications. In this demonstration, we present HighFiveLive, a smartwatch application that uses data from an onboard accelerometer to detect and classify fine-grained symbolic gestures, which convey semantic meaning and have social significance. We apply logistic regression to learn a representative model of 9 symbolic gestures as performed by 32 users; in an offline evaluation study, the model accurately classifies 92% of recognized gestures. Building on this work, we deploy the learned model in our HighFiveLive mobile application, which detects and classifies symbolic gestures in real-time as they are performed. HighFiveLive is implemented as an Android application with connection to a wrist-worn accelerometer stream (such as a Microsoft Band) as well as a standalone Apple Watch application.
UR - https://www.scopus.com/pages/publications/84966546889
UR - https://www.scopus.com/pages/publications/84966546889#tab=citedBy
U2 - 10.1109/PERCOMW.2016.7457072
DO - 10.1109/PERCOMW.2016.7457072
M3 - Conference contribution
AN - SCOPUS:84966546889
T3 - 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
BT - Proceedings - 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 March 2016 through 18 March 2016
ER -