Clothing-based person clustering in family photos

This paper presents methods to explore and fuse various clothing features for person clustering in family photos. Our approach automatically detects the clothing regions, extracts the global and localized features based on color and texture, and then computes multiple partitions of people based on different features, which are combined into the final consolidated person clustering with a cluster ensemble technique. The clothing clusters can be used for complementing face clusters and for other photo organization applications. The effectiveness of our approach is tested on real-world family photo datasets.