@inproceedings{9a3bd98f3fd844c0b09e853cbc2c7f15,
title = "Gesture-based control in a smart home environment",
abstract = "Gesture is a convenient and natural way to control a smart home. The wearable device provides an excellent vehicle for getting a user's hand gesture. Recognition models for gestures can be divided into two types: user dependent and user independent. In this research, we propose a hybrid model that combines both user dependent and user independent models to distinguish a user's hand gestures. Our research investigates which model among three is the best approach for recognizing hand gestures. We employ ten hand gestures as the test cases for comparison. First, from a 6-axis wearable device we extract features based on the collected raw data of hand gestures. Then these extracted features are analyzed by a oneM2M-compliant platform to detect gestures based on Decision Tree and Logistic Regression algorithms. With a data set of over 7 users and 20 repetitions of tests for each user, we tested the effectiveness of recognition models and gesture detection algorithms. The results show that our proposed hybrid model could achieve the best accuracy with either of two detection algorithms.",
keywords = "Gesture recognition, OneM2M, Recognition model, Smart home",
author = "Fariz Alemuda and Fuchun Lin",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; Joint 10th IEEE International Conference on Internet of Things, iThings 2017, 13th IEEE International Conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International Conference on Smart Data, Smart Data 2017 ; Conference date: 21-06-2017 Through 23-06-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/iThings-GreenCom-CPSCom-SmartData.2017.120",
language = "English",
series = "Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "784--791",
editor = "Yulei Wu and Geyong Min and Nektarios Georgalas and Ahmed Al-Dubi and Xiaolong Jin and Yang, {Laurence T.}",
booktitle = "Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017",
address = "美國",
}
