AN INTERACTIVE FRAMEWORK FOR UNDERSTANDING USER'S PERCEPTION OF MULTIMEDIA DATA

摘要

A methodology of highly interactive intra-object relevance feedback is used to retrieve images from a database. The query is adjusted using the information fed-back by the user about the relevance of previously extracted part(s) from the object itself, such that the adjusted query is a better approximation to the user's perception. Since a single query image is utilized in the system according to the invention, high-performance learning techniques can be employed for this intra-object learning of user's perception. The refined query is subsequently used for intra-object relevance feedback where images are retrieved from the database based on parameters learnt by intra-image feedback mechanism, and the user provides feedback by ranking the retrieved objects in order of their relevance to him or her. In the system according to the invention, intraobject learning of user's perception is expedited by utilizing the learnt parameters in the intra-object relevance feedback. Furthermore, the methodology of the invention allows for building refined queries based on part(s) of the query object rather than the entire object itself, thereby reducing the number of irrelevant objects, retrieved from the database.