Bayesian sensing hidden markov model for hand gesture recognition

Ari Hernawan, Yuan Shan Lee, Andri Santoso, Chien Yao Wang, Jia Ching Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

This paper proposes a modified Bayesian Sensing Hidden Markov Model (BS-HMM) to address the problem of hand gestures recognition on few labeled data. In this work, BS-HMM is investigated based on its success to address the problem of largevocabulary of continuous speech recognition. We introduced error modeling into BS-HMM basis vector to handle the noise that occurs in the data. We also introduced a forgetting factor to preserve important information from previous basis vector and to improve both convergence and representation ability of the BS-HMM basis vector. We modified Moving Pose method to extract the feature descriptor from hand gestures data. To evaluate the performance of our system, we compared our proposed method with previously proposed HMM methods. The experimental result showed the improvement of proposed method over others, even when only a small number of labeled data are available for training dataset.

原文???core.languages.en_GB???
主出版物標題Proceedings of the ASE BigData and SocialInformatics 2015, ASE BD and SI 2015
發行者Association for Computing Machinery
ISBN(電子)9781450337359
DOIs
出版狀態已出版 - 7 10月 2015
事件ASE BigData and SocialInformatics, ASE BD and SI 2015 - Kaohsiung, Taiwan
持續時間: 7 10月 20159 10月 2015

出版系列

名字ACM International Conference Proceeding Series
07-09-Ocobert-2015

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???event.eventtypes.event.conference???ASE BigData and SocialInformatics, ASE BD and SI 2015
國家/地區Taiwan
城市Kaohsiung
期間7/10/159/10/15

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