TY - GEN
T1 - Wearable air-writing recognition system employing dynamic time warping
AU - Luo, Yuqi
AU - Liu, Jiang
AU - Shimamoto, Shigeru
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/9
Y1 - 2021/1/9
N2 - Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field. In this paper, we propose a wearable air-writing system that makes users can write the English alphabet in the three-dimensional space without any write rules. The proposed system is based on the Inertial Measurement Unit (IMU), and it uses dynamic time warping (DTW) as the main recognition algorithm. In addition, to improve the recognition accuracy and take a better advantage of the DTW algorithm, we present an adjustment system that gives some new optimization methods to the application of IMU and DTW. In the experiment, the accuracy of recognition is 84.6% for the uppercase alphabet (from 'A' to 'Z') in user-dependent case. And we also confirmed that the recognition method only based on the DTW algorithm is one kind of user-dependent methods, which means this method is heavily dependent on personalization.
AB - Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field. In this paper, we propose a wearable air-writing system that makes users can write the English alphabet in the three-dimensional space without any write rules. The proposed system is based on the Inertial Measurement Unit (IMU), and it uses dynamic time warping (DTW) as the main recognition algorithm. In addition, to improve the recognition accuracy and take a better advantage of the DTW algorithm, we present an adjustment system that gives some new optimization methods to the application of IMU and DTW. In the experiment, the accuracy of recognition is 84.6% for the uppercase alphabet (from 'A' to 'Z') in user-dependent case. And we also confirmed that the recognition method only based on the DTW algorithm is one kind of user-dependent methods, which means this method is heavily dependent on personalization.
KW - Air-writing
KW - Dynamic time warping
KW - Gesture recognition
KW - Human computer interaction
KW - IMU
KW - Wearable devices
UR - http://www.scopus.com/inward/record.url?scp=85102982336&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102982336&partnerID=8YFLogxK
U2 - 10.1109/CCNC49032.2021.9369458
DO - 10.1109/CCNC49032.2021.9369458
M3 - Conference contribution
AN - SCOPUS:85102982336
T3 - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
BT - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
Y2 - 9 January 2021 through 13 January 2021
ER -