Multiclass Recognition with Multiple Feature Trees

摘要

This paper proposes a multiclass recognition scheme which uses multiple feature trees with anextended scoring method evolved from TF-IDF. Feature trees consisting of different featuredescriptors such as SIFT and SURF are built by the hierarchical k-means algorithm. Theexperimental results show that the proposed scoring method combing with the proposedmultiple feature trees yields high accuracy for multiclass recognition and achieves significantimprovement compared to methods using a single feature tree with original TF-IDF.