IntentSearch: Capturing User Intention for One-Click Internet Image Search

—Web-scale image search engines (e.g. Google Image Search, Bing Image Search) mostly rely on surrounding text features. It is difficult for them to interpret users’ search intention only by query keywords and this leads to ambiguous and noisy search results which are far from satisfactory. It is important to use visual information in order to solve the ambiguity in text-based image retrieval. In this paper, we propose a novel Internet image search approach. It only requires the user to click on one query image with the minimum effort and images from a pool retrieved by text-based search are re-ranked based on both visual and textual content. Our key contribution is to capture the users’ search intention from this one-click query image in four steps. (1) The query image is categorized into one of the predefined adaptive weight categories, which reflect users’ search intention at a coarse level. Inside each category, a specific weight schema is used to combine visual features...

• Type: Journal
• Year: 2012
• Where: PAMI
• Authors: Xiaoou Tang, Ke Liu, Jingyu Cui, Fang Wen, Xiaogang Wang
• Keywords: Google Image Search, Image Search Engines, PAMI 2012, Similarity Metrics, Software Engineering