A Comparison of Active Classification Methods for Content-Based Image Retrieval

Philippe-Henri Gosselin (1) , Matthieu Cord (2)

1 MIDI - Multimedia Indexation and Data Integration
2 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes

This paper deals with content-based image indexing and category retrieval in general databases. Statistical learning approaches have been recently introduced in CBIR. Labelled images are considered as training data in learning strategy based on classification process. We introduce an active learning strategy to select the most difficult images to classify with only few training data. Experimentations are carried out on the COREL database. We compare seven clas- sification strategies to evaluate the active learning contribution in CBIR.

Domains: Machine Learning [stat.ML]

Philippe-Henri Gosselin, Matthieu Cord. A Comparison of Active Classification Methods for Content-Based Image Retrieval. International Workshop on Computer Vision meets Databases, ACM Sigmod, Jun 2004, France. pp.1. ⟨hal-00520318⟩