Image Content Clustering and Summarization for Photo Collections

Rapid growth of digital photography in recent years spurred the need of photo management tools. In this study, we propose an automatic organization framework for photo collections based on image content, so that a novel browsing experience is provided for users. For each photograph, human faces, together with corresponding clothes and nearby regions are located. We extract color histograms of these regions as the image content feature. Then a similarity matrix of a photo collection is generated according to temporal and content features of those photographs. We perform hierarchical clustering based on this matrix, and extract duplicate subjects of a cluster by introducing the contrast context histogram (CCH) technique. The experimental results show that the developed framework provides a promising result for photo management