Semi-supervised Spectral Clustering for Image Set Classification

CVPR 2014 Arif MahmoodAjmal MianRobyn Owens

We present an image set classification algorithm based on unsupervised clustering of labeled training and unlabeled test data where labels are only used in the stopping criterion. The probability distribution of each class over the set of clusters is used to define a true set based similarity measure... (read more)

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