  In this paper, we consider the clustering problem on images where each image
contains patches in people and location domains. We exploit the correlation
between people and location domains, and proposed a semi-supervised
co-clustering algorithm to cluster images. Our algorithm updates the
correlation links at the runtime, and produces clustering in both domains
simultaneously. We conduct experiments in a manually collected dataset and a
Flickr dataset. The result shows that the such correlation improves the
clustering performance.
