An interactive approach to image retrieval using multiple seed images
The concept, procedure and tools for interactive image retrieval with multiple seed images are investigated in this research. Specifically, we consider an interactive query process in which the query can be refined so that the meaning of "similarity": defined by a specific user for a particular application can be approached gradually. This idea is implemented by performing adaptive filtering with multiple low level indexing features based on user's feedback. The proposed approach is demonstrated by a testbed with flexible query formation, efficient initial guess and further refinement tools.