Combining search results from multimedia sources is crucial for dealing with heterogeneous multimedia data, particularly in multimedia retrieval where a final ranked list of items of interest is returned sorted by confidence or relevance. However, relatively little attention has been given to combination functions, especially their upper bound performance limits. This paper presents a theoretical framework for studying upper bounds for two types of combination functions. A general upper bound and two approximations are proposed for monotonic combination functions. We also studied the upper bounds for linear combination functions using a global optimization technique. Our experimental results show that the choice of combination functions has a considerable influence to retrieval performance.
Rong Yan, Alexander G. Hauptmann