Home Photo Categorization Based on Photographic Region Templates

In this paper, we propose new photo categorization which is suitable for a home photo album. To enhance the categorization, both local and global concepts of the photos are modeled and their combined concept learning method for the photo categorization is proposed. The local and global concepts are trained by individual support vector machines. Region templates for the local concepts of generic home photos are proposed. Further, local concepts are merged with confidence to lead to the global concept to achieve reliable categorization. Experiment results show that the proposed method is useful to detect multi-category concepts for the home photo album.