Kernels on Bags of Fuzzy Regions for Fast Object retrieval

We propose in this paper a general kernel framework to deal with database object retrieval embedded in images with heterogeneous background. We use local features computed on fuzzy regions for image representation summarized in bags, and we propose original kernel functions to deal with sets of features and spatial constraints. Combined with SVMs classification and online learning scheme, the resulting algorithm satisfies the robustness requirements for representation and classification of objects. Experiments on a specific database having objects with heterogeneous backgrounds show the performance of our object retrieval technique.