Tag-based Web Photo Retrieval Improved by Batch Mode Re-Tagging

Web photos in social media sharing websites such as Flickr are generally accompanied by rich but noisy textual descriptions (tags, captions, categories, etc.). In this paper, we proposed a tag-based photo retrieval framework to improve the retrieval performance for Flickr photos by employing a novel batch mode re-tagging method. The proposed batch mode re-tagging method can automatically refine noisy tags of a group of Flickr photos uploaded by the same user within a short period by leveraging millions of training web images and their associated rich textual descriptions. Specifically, for one group of Flickr photos, we construct a group-specific lexicon which contains only the tags of all photos within the group. For each query tag, we employ the inverted file method to automatically find loosely labeled training web images. We propose a SVM with Augmented Features, referred to as AFSVM, to learn adapted classifiers to refine the annotation tags of photos by leveraging the exi...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Lin Chen, Dong Xu, Wai-Hung Tsang, Jiebo Luo
• Keywords: Computer Vision, CVPR 2010, Flickr Photos, Mode Re-tagging Method, Training Web Images