Skip to Main content Skip to Navigation
Conference papers

Kernel on Bags for multi-object database retrieval.

Abstract : In this paper, a kernel-based method for multi-object re- trieval in large image database is presented. First, our approach exploits a fuzzy region segmentation ap- proach in order to get robust local feature extraction and characterization. All the region features are summarized in bags representing the image index. The main part of this work concerns the kernel functions to deal with sets of fea- tures. Based on the linear combination of minor kernels, a family of kernels on bags is introduced. Several weighting schemes and combinations are proposed. Their introduction are motivated in the specific context of dealing with multi- object recognition with heterogeneous background. Com- bined with SVMs classification and interactive online learn- ing framework, the resulting algorithm satisfies the robust- ness requirements for representation and classification of ob- jects. Experiments and comparisons demonstrate the good performances of our multi-object retrieval technique.
Document type :
Conference papers
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download
Contributor : Philippe-Henri Gosselin <>
Submitted on : Wednesday, September 22, 2010 - 7:00:13 PM
Last modification on : Monday, January 25, 2021 - 3:16:02 PM
Long-term archiving on: : Thursday, December 23, 2010 - 3:17:36 AM


Publisher files allowed on an open archive



Philippe-Henri Gosselin, Matthieu Cord, Sylvie Philipp-Foliguet. Kernel on Bags for multi-object database retrieval.. ACM International Conference on Image and Video Retrieval, Jul 2007, Amsterdam, Netherlands. pp.226-231, ⟨10.1145/1282280.1282317⟩. ⟨hal-00520303⟩



Record views


Files downloads