FADA

An efficient dimension reduction scheme for image classification

Yijuan Lu, Jingsheng Ma, Qi Tian

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper develops a novel and efficient dimension reduction scheme-Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sample distributions and discover the classification in the subspace with naïve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is tested and evaluated using synthetic dataset, COREL dataset and three different face datasets. The experimental results show FADA is more effective and computationally more efficient than ADA for image classification. © Springer-Verlag Berlin Heidelberg 2007.

    Original languageEnglish
    Title of host publicationAdvances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings
    Pages1-9
    Number of pages9
    Volume4810 LNCS
    Publication statusPublished - 2007
    Event8th Pacific-Rim Conference on Multimedia - Hong Kong, Hong Kong
    Duration: 11 Dec 200714 Dec 2007

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4810 LNCS
    ISSN (Print)0302-9743

    Conference

    Conference8th Pacific-Rim Conference on Multimedia
    Abbreviated titlePCM 2007
    CountryHong Kong
    CityHong Kong
    Period11/12/0714/12/07

    Fingerprint

    Image classification
    Discriminant analysis
    Classifiers

    Keywords

    • Adaptive discriminant analysis
    • Image classification

    Cite this

    Lu, Y., Ma, J., & Tian, Q. (2007). FADA: An efficient dimension reduction scheme for image classification. In Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings (Vol. 4810 LNCS, pp. 1-9). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4810 LNCS).
    Lu, Yijuan ; Ma, Jingsheng ; Tian, Qi. / FADA : An efficient dimension reduction scheme for image classification. Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings. Vol. 4810 LNCS 2007. pp. 1-9 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    @inproceedings{19f592e1a97446df84ac21482cb8f174,
    title = "FADA: An efficient dimension reduction scheme for image classification",
    abstract = "This paper develops a novel and efficient dimension reduction scheme-Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sample distributions and discover the classification in the subspace with na{\"i}ve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is tested and evaluated using synthetic dataset, COREL dataset and three different face datasets. The experimental results show FADA is more effective and computationally more efficient than ADA for image classification. {\circledC} Springer-Verlag Berlin Heidelberg 2007.",
    keywords = "Adaptive discriminant analysis, Image classification",
    author = "Yijuan Lu and Jingsheng Ma and Qi Tian",
    year = "2007",
    language = "English",
    isbn = "9783540772545",
    volume = "4810 LNCS",
    series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    pages = "1--9",
    booktitle = "Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings",

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    Lu, Y, Ma, J & Tian, Q 2007, FADA: An efficient dimension reduction scheme for image classification. in Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings. vol. 4810 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4810 LNCS, pp. 1-9, 8th Pacific-Rim Conference on Multimedia, Hong Kong, Hong Kong, 11/12/07.

    FADA : An efficient dimension reduction scheme for image classification. / Lu, Yijuan; Ma, Jingsheng; Tian, Qi.

    Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings. Vol. 4810 LNCS 2007. p. 1-9 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4810 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    TY - GEN

    T1 - FADA

    T2 - An efficient dimension reduction scheme for image classification

    AU - Lu, Yijuan

    AU - Ma, Jingsheng

    AU - Tian, Qi

    PY - 2007

    Y1 - 2007

    N2 - This paper develops a novel and efficient dimension reduction scheme-Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sample distributions and discover the classification in the subspace with naïve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is tested and evaluated using synthetic dataset, COREL dataset and three different face datasets. The experimental results show FADA is more effective and computationally more efficient than ADA for image classification. © Springer-Verlag Berlin Heidelberg 2007.

    AB - This paper develops a novel and efficient dimension reduction scheme-Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sample distributions and discover the classification in the subspace with naïve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is tested and evaluated using synthetic dataset, COREL dataset and three different face datasets. The experimental results show FADA is more effective and computationally more efficient than ADA for image classification. © Springer-Verlag Berlin Heidelberg 2007.

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    KW - Image classification

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    M3 - Conference contribution

    SN - 9783540772545

    VL - 4810 LNCS

    T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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    BT - Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings

    ER -

    Lu Y, Ma J, Tian Q. FADA: An efficient dimension reduction scheme for image classification. In Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings. Vol. 4810 LNCS. 2007. p. 1-9. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).