Inexact graph matching based on kernels for object retrieval in image databases |
| |
Authors: | Justine LebrunPhilippe-Henri Gosselin Sylvie Philipp-Foliguet |
| |
Affiliation: | ETIS, CNRS, ENSEA, Univ Cergy-Pontoise, F-95000 Cergy-Pontoise, France |
| |
Abstract: | In the framework of online object retrieval with learning, we address the problem of graph matching using kernel functions. An image is represented by a graph of regions where the edges represent the spatial relationships. Kernels on graphs are built from kernel on walks in the graph. This paper firstly proposes new kernels on graphs and on walks, which are very efficient for graphs of regions. Secondly we propose fast solutions for exact or approximate computation of these kernels. Thirdly we show results for the retrieval of images containing a specific object with the help of very few examples and counter-examples in the framework of an active retrieval scheme. |
| |
Keywords: | Online Interactive Database Content-based Object retrieval Image retrieval Machine learning Kernel methods Graph matching Inexact match |
本文献已被 ScienceDirect 等数据库收录! |