Modeling User Feedback Using a Hierarchical Graphical Model for Interactive Image Retrieval

Relevance feedback is an important mechanism for narrowing the semantic gap in content-based image retrieval and the process involves the user labeling positive and negative images. Very often, it is some specific objects or regions in the positive feedback images that the user is really interested in rather than the entire image. This paper presents a hierarchical graphical model for automatically extracting objects and regions that the user is interested in from the positive images which in turn are used to derive features that better reflect the user’s feedback intentions for improving interactive image retrieval. The novel hierarchical graphical model embeds image formation prior, user intention prior and statistical prior in its edges and uses a max-flow/min-cut method to simultaneously segment all positive feedback images into user interested and user uninterested regions. An important innovation of the

• Type: Conference
• Year: 2007
• Where: PCM
• Authors: Jian Guan, Guoping Qiu
• Keywords: Hierarchical Graphical Model, Multimedia, PCM 2007, Positive Feedback Images, User