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Guo et al., 2019 - Google Patents

Robust low-rank subspace segmentation with finite mixture noise

Guo et al., 2019

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Document ID
9825034702972831646
Author
Guo X
Xie X
Liu G
Wei M
Wang J
Publication year
Publication venue
Pattern Recognition

External Links

Snippet

Subspace segmentation or clustering remains a challenge of interest in computer vision when handling complex noise existing in high-dimensional data. Most of the current sparse representation or minimum-rank based techniques are constructed on ℓ 1-norm or ℓ 2-norm …
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Classifications

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    • 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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