Class consistent k-means: Application to face and action recognition

TitleClass consistent k-means: Application to face and action recognition
Publication TypeJournal Articles
Year of Publication2012
AuthorsZhuolin Jiang, Lin Z, Davis LS
JournalComputer Vision and Image Understanding
Pagination730 - 741
Date Published2012/06//
ISBN Number1077-3142
KeywordsAction recognition, Class consistent k-means, Discriminative tree classifier, face recognition, Supervised clustering

A class-consistent k-means clustering algorithm (CCKM) and its hierarchical extension (Hierarchical CCKM) are presented for generating discriminative visual words for recognition problems. In addition to using the labels of training data themselves, we associate a class label with each cluster center to enforce discriminability in the resulting visual words. Our algorithms encourage data points from the same class to be assigned to the same visual word, and those from different classes to be assigned to different visual words. More specifically, we introduce a class consistency term in the clustering process which penalizes assignment of data points from different classes to the same cluster. The optimization process is efficient and bounded by the complexity of k-means clustering. A very efficient and discriminative tree classifier can be learned for various recognition tasks via the Hierarchical CCKM. The effectiveness of the proposed algorithms is validated on two public face datasets and four benchmark action datasets.