Multi-model similarity propagation and its application for web image retrieval

Xin-Jing Wang, Wei-Ying Ma, Gui-Rong Xue, Xing Li
2004 Proceedings of the 12th annual ACM international conference on Multimedia - MULTIMEDIA '04  
In this paper, we propose an iterative similarity propagation approach to explore the inter-relationships between Web images and their textual annotations for image retrieval. By considering Web images as one type of objects, their surrounding texts as another type, and constructing the links structure between them via webpage analysis, we can iteratively reinforce the similarities between images. The basic idea is that if two objects of the same type are both related to one object of another
more » ... object of another type, these two objects are similar; likewise, if two objects of the same type are related to two different, but similar objects of another type, then to some extent, these two objects are also similar. The goal of our method is to fully exploit the mutual reinforcement between images and their textual annotations. Our experiments based on 10,628 images crawled from the Web show that our proposed approach can significantly improve Web image retrieval performance. In this paper, we attempt to learn the semantic similarities of images using the relations between Web images and their textual annotations. We propose a method called Iterative Similarity Propagation which iteratively reinforces the similarities between images by their textual annotations, and vice versa. Our goal is to explore the interrelation between multiple modalities, and by this way, to discover the intrinsic similarity of images and improve the
doi:10.1145/1027527.1027746 dblp:conf/mm/WangMXL04 fatcat:2dqpqm3ogjbjjkjszwp2euw62q