Multimodal belief integration by HMM/SVM-embedded bayesian network: Applications to ambulating pc operation by body motions and brain signals

Yasuo Matsuyama*, Fumiya Matsushima, Youichi Nishida, Takashi Hatakeyama, Nimiko Ochiai, Shogo Aida

*この研究の対応する著者

    研究成果

    3 被引用数 (Scopus)

    抄録

    Methods to integrate multimodal beliefs by Bayesian Networks (BNs) comprising Hidden Markov Models (HMMs) and Support Vector Machines (SVMs) are presented. The integrated system is applied to the operation of ambulating PCs (biped humanoids) across the network. New features in this paper are twofold. First, the HMM/SVM-embedded BN for the multimodal belief integration is newly presented. Its subsystem also has a new structure such as a committee SVM array. Another new fearure is with the applications. Body and brain signals are applied to the ambulating PC operation by using the recognition of multimodal signal patterns. The body signals here are human gestures. Brain signals are either HbO2 of NIRS or neural spike trains. As for such ambulating PC operation, the total system shows better performance than HMM and BN systems alone.

    本文言語English
    ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    ページ767-778
    ページ数12
    5768 LNCS
    PART 1
    DOI
    出版ステータスPublished - 2009
    イベント19th International Conference on Artificial Neural Networks, ICANN 2009 - Limassol
    継続期間: 2009 9 142009 9 17

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    番号PART 1
    5768 LNCS
    ISSN(印刷版)03029743
    ISSN(電子版)16113349

    Other

    Other19th International Conference on Artificial Neural Networks, ICANN 2009
    CityLimassol
    Period09/9/1409/9/17

    ASJC Scopus subject areas

    • コンピュータ サイエンス(全般)
    • 理論的コンピュータサイエンス

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