Region-based image annotation of graph learning approach

Abstract

Image annotation has been an active research topic in recent years.The authors formulated image annotation as a semi-supervised learning problem under multi-instance learning framework.A novel graph-based semi-supervised learning approach to image annotation,using multiple instances,was presented,which extended the conventional semi-supervised learning to multi-instance setting by introducing the adaptive geometric relationship between two bags of instances.The experimental results show that this approach outperforms other traditional methods and is effective for image annotation.