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Hu et al., 2016 - Google Patents

Multi-manifolds discriminative canonical correlation analysis for image set-based face recognition

Hu et al., 2016

Document ID
13676834589472159059
Author
Hu H
Gu J
Publication year
Publication venue
Cognitive Computation

External Links

Snippet

In this paper, multi-manifolds discriminative canonical correlation analysis (MMDCCA) is presented for solving face recognition problem with using different image sets. We adopt Linearity-Constrained Hierarchical Agglomerative Clustering algorithm for dividing all image …
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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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
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    • G—PHYSICS
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