Distance metric learning from uncertain side information with application to automated photo tagging

Automated photo tagging is essential to make massive unlabeled photos searchable by text search engines. Conventional image annotation approaches, though working reasonably well on small testbeds, are either computationally expensive or inaccurate when dealing with large-scale photo tagging. Recently, with the popularity of social networking websites, we observe a massive number of user-tagged images, referred to as “social images”, that are available on the web. Unlike traditional web images, social images often contain tags and other user-generated content, which offer a new opportunity to resolve some long-standing challenges in multimedia. In this work, we aim to address the challenge of large-scale automated photo tagging by exploring the social images. We present a retrieval based approach for automated photo tagging. To tag a test image, the proposed approach first retrieves k social images that share the largest visual similarity with the test image. The tags of the test...

• Type: Conference
• Year: 2009
• Where: MM
• Authors: Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
• Keywords: MM 2009, Photo, Social Image, Test Image