PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Multiple Kernel Learning via Distance Metric Learning for Interactive Image Retrieval
Fei Yan, Krystian Mikolajczyk and Josef Kittler
In: International Workshop on Multiple Classifier Systems, 15-17 Jun 2011, Naples, Italy.


In this paper we formulate multiple kernel learning (MKL) as a distance metric learning (DML) problem. More specifically, we learn a linear combination of a set of base kernels by optimising two objective functions that are commonly used in distance metric learning. We first propose a global version of such an MKL via DML scheme, then a localised version. We argue that the localised version not only yields better performance than the global version, but also fits naturally into the framework of example based retrieval and relevance feedback. Finally the usefulness of the proposed schemes are verified through experiments on two image retrieval datasets.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:8287
Deposited By:Fei Yan
Deposited On:22 July 2011