Hierarchical image modeling for object-based media retrieval

Images are more structurally complex than the data stored in the traditional DBMSs. Many systems perform media retrieval based on image feature matching; the fact that images have structures is ignored. On the other hand, we view images as compound objects containing many component objects. Each component object corresponds to a region(s) that is a visually and semantically meaningful entity (e.g. car, man, etc.). As images/objects truly have hierarchical structures and have both visual and semantics properties, we argue that image retrieval using either semantics and image matching alone is insufficient. In this paper, we introduce a hierarchical structure for image modeling to support image retrieval using combinations of semantic expressions and visual examples at both the whole image and object levels. We give formal definitions of a multimedia query language and a system implementation based on this image modeling. We also address associated query processing issues and discuss the portability and extendibility of our approach.