Audio-visual recognition system with intra-modal fusion

Yee Wan Wong, Kah Phooi Seng, Li Minn Ang, Wan Yong Khor, Heng Fui Liau

    Research output: Book chapter/Published conference paperConference paperpeer-review

    6 Citations (Scopus)

    Abstract

    In this paper, a new multimodal biometric recognition system based on feature fusion is proposed to increase the robustness and circumvention of conventional multimodal recognition system. The feature sets originating from the output of the visual and audio feature extraction systems are fused and being classified by RBF neural network. Other than that, 2DPCA is proposed to work in conjunction with LDA to further increase the recognition performance of the visual recognition system. The experimental result shows that the proposed system achieves a higher recognition rate as compared to the conventional multimodal recognition system. Besides, we also show that the 2DPCA +LDA achieves a higher recognition rate as compared with PCA, PCA+LDA and 2DPCA.

    Original languageEnglish
    Title of host publicationProceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007
    Pages609-613
    Number of pages5
    DOIs
    Publication statusPublished - 01 Dec 2007
    Event2007 International Conference on Computational Intelligence and Security, CIS'07 - Harbin, Heilongjiang, China
    Duration: 15 Dec 200719 Dec 2007

    Conference

    Conference2007 International Conference on Computational Intelligence and Security, CIS'07
    Country/TerritoryChina
    CityHarbin, Heilongjiang
    Period15/12/0719/12/07

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