Efficient cross-domain image retrieval by multi-level matching and spatial verification for structural similarity
Journal
2014 ACM Multimedia Conference
Pages
1185-1188
ISBN
9781450330633
Date Issued
2014
Author(s)
Abstract
Content-based image retrieval (CBIR) technique is important for browsing the rapidly growing Web images. However, traditional CBIR methods usually fail when the query and database images are in different domains. Instead of focusing on a specific domain, we propose a method to solve the general cross-domain image retrieval problem. This method focuses on the structure of image content but not the detail at pixel level, so it is particularly useful for matching the images across different visual domains e.g., paintings, hand-drawn sketches or photographs. To provide an efficient and effective solution, we analyze the bag-of-words (BoW) matching procedure to find out what causing it to fail in the cross-domain setting. We observe that it is necessary to apply different matching constraints for cross-domain image retrieval; therefore, we propose a multi-level matching process which dynamically selects the most suitable matching constraint for feature matching and adopt a fast spatial verification to describe the structure similarity. Finally, our method is much faster than the state-of-the-art solution and achieves better performance in the experiments.
Subjects
Cross-domain; Image retrieval; Multilevel matching; Spatial verification
Type
conference paper