Image annotation based on recommendation model

Authors:
Zijia Lin;Guiguang Ding;Jianmin Wang
Affiliations:
School of Software, Tsinghua University, Beijing, China;School of Software, Tsinghua University, Beijing, China;School of Software, Tsinghua University, Beijing, China
Venue:
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Year:
2011

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Abstract

In this paper, a novel approach based on recommendation model is proposed for automatic image annotation. For any to-be-annotated image, we first select some related images with tags from training dataset according to their visual similarity. And then we estimate the initial ratings for tags of the training images based on tag ranking method and construct a rating matrix. We also construct a trust matrix based on visual similarity with a k-NN strategy. Then a recommendation model is built on both matrices to rank candidate tags for the target image. The proposed approach is evaluated using two benchmark image datasets, and experimental results have indicated its effectiveness.