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Li et al., 2022 - Google Patents

Multi-level Fisher vector aggregated completed local fractional order derivative feature vector for face recognition

Li et al., 2022

Document ID
9135943945799360106
Author
Li J
Chen Y
Zhang E
Publication year
Publication venue
Multimedia Systems

External Links

Snippet

In this paper, we propose an image feature extraction method, multi-level Fisher vector aggregated completed local fractional order derivative feature vector (mFVFD), for face recognition. The novelties of our method are summarized as follows:(1) We propose multi …
Continue reading at link.springer.com (other versions)

Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
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