@inproceedings{1f314940b2c3489eb117de5509eb8eda,
title = "Gesture Recognition Based on Deep Belief Networks",
abstract = "Analyzing the data acquired from the inertial sensor in mobile phones has been proved to be an effective way in gesture recognition. This research introduces deep belief networks (DBN) to solve the inertial sensor-based gesture recognition problem and obtains a satisfactory result on the BUAA Mobile Gesture Database. The optimal architecture and the hyper parameters of DBN were tuned according to the performance of experiments in order to get a high recognition accuracy within short time. Besides, three state-of-the-art methods were tested on the same database and the comparison of results indicates that the proposed method achieved a much better recognition accuracy, which considerably improves the recognition performance.",
keywords = "Deep belief networks, Deep learning, Gesture recognition",
author = "Yunqi Miao and Linna Wang and Chunyu Xie and Baochang Zhang",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 12th Chinese Conference on Biometric Recognition, CCBR 2017 ; Conference date: 28-10-2017 Through 29-10-2017",
year = "2017",
doi = "10.1007/978-3-319-69923-3\_47",
language = "英语",
isbn = "9783319699226",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "439--446",
editor = "Yunhong Wang and Yu Qiao and Jie Zhou and Jianjiang Feng and Zhenan Sun and Zhenhua Guo and Shiguang Shan and Linlin Shen and Shiqi Yu and Yong Xu",
booktitle = "Biometric Recognition - 12th Chinese Conference, CCBR 2017, Proceedings",
address = "德国",
}