Learning Concept Templates from Web Images to Query Personal Image Databases

With the proliferation of digital cameras, the size of personal media data such as digital photos, videos, etc. has grown extremely large. The personal nature of the data has heightened the demands for a media management system on personal desktops. Existing solutions for media management target mostly server-based Web databases and rely on extensive metadata (i.e., labels) generation to aid retrieval. Personal media databases, on the other hand, have very limited labels generated by the end users themselves. This paper introduces a method for learning concept templates from web images to query personal image databases. The proposed method has the advantage of leveraging Web resources to ease personal photo retrieval in order to avoid costly annotation of personal image databases.