Names and Faces in the News Abstract

"Names and Faces in the News Abstract," Miller, CVPR, 2004

The paper presents a clustering method to deal with ambiguities in labeling and identify incorrectly labeled faces.

Before clustering, they perform kernel PCA to reduce the dimensionality and linear discriminant analysis to project data for discriminant analysis.

The clustering process goes as following:
1.Randomly assign each image to one of its extracted names.
2.For each distinct name (cluster), calculate the mean of image vectors assigned to that name.
3. Reassign each image to the closest mean of its extracted names.
4. Repeat 2-3 until convergence (i.e. no image changes names during an iteration)

Next, do cluster pruning for meaningless clusters according to likelihood. If there are some clusters which have similar compositions, merge them and get the final clusters. In the experiment, they success in cleaning up noisy unsupervised data and use entropy to evaluate the result.