Multiple-Instance Image Database Retrieval by Spatial Similarity Based on Interval Neighbor Group

edu.tw In this paper, a multiple-instance image retrieval system incorporating a general spatial similarity measure is proposed. A multiple-instance learning is employed to summarize the commonality of spatial features among positive and negative example images. The general spatial similarity measure evaluates the degree of similarity between matching atomic spatial relations present in the maximum common object set of the query and a database image based on their nodal distance in an Interval Neighbor Group (ING). The shorter the distance, the higher degree of similarity, while a longer one, a lower degree of similarity. An ensemble similarity measure, derived from the spatial relations of all constituent objects in the query and a database image, will then integrate these atomic spatial similarit