A Unified Optimization Based Learning Method for Image Retrieval

Hanghang Tong, Jingrui He, Mingjing Li, Wei-Ying Ma, Changshui Zhang, Hong-Jiang Zhang
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)  
In this paper, an optimization based learning method is proposed for image retrieval from graph model point of view. Firstly, image retrieval is formulated as a regularized optimization problem, which simultaneously considers the constraints from low-level feature, online relevance feedback and offline semantic information. Then, the global optimal solution is developed in both closed form and iterative form, providing that the latter converges to the former. The proposed method is unified in
more » ... hod is unified in the senses that 1) it makes use of the information from various aspects in a global optimization manner so that the retrieval performance might be maximally improved; 2) it provides a natural way to support two typical query scenarios in image retrieval. The proposed method has a solid mathematical ground. Systematic experimental results on a general-purpose image database demonstrate that it achieves significant improvements over existing methods.
doi:10.1109/cvpr.2005.54 dblp:conf/cvpr/TongHLMZZ05 fatcat:idaigrtborhu3dn5uoku5meipu