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Cheng et al., 2009 - Google Patents

Kernel PCA of HOG features for posture detection

Cheng et al., 2009

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Document ID
6609973590360504663
Author
Cheng P
Li W
Ogunbona P
Publication year
Publication venue
2009 24th International Conference Image and Vision Computing New Zealand

External Links

Snippet

Motivated by the non-linear manifold learning ability of the kernel principal component analysis (KPCA), we propose in this paper a method for detecting human postures from single images by employing KPCA to learn the manifold span of a set of HOG features that …
Continue reading at core.ac.uk (PDF) (other versions)

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