Automatic face-based image grouping for albuming

In this paper, a system for automatic albuming of consumer photographs is described, that uses face-based information extracted from images. The target image sets for this work are snapshots from family photo collections. The aim is to automatically provide the user with the option of selecting image groups based on the people present in them. The core components of age/gender classification and clustering based on facial similarity for this domain are discussed. Age and gender classification based on individual facial feature measurements combined to produce a single classifier using the AdaBoost algorithm. Face-based information is used both in locating suitable images and layout/design phases of the albuming process. Face-based information is combined with earlier work on event segmentation and layout design to provide a more effective system. Performance is tested on two family photo databases covering a 5 year time-span.