Guess what you draw: interactive contour-based image retrieval on a million-scale database

We propose a real-time image retrieval system which allows users to search target images whose objects are similar to the query in contour, regardless of their sizes and positions appearing in the images. Even in a complicated scene, as long as the object's contour is most salient in the target image, the system is still able to capture it and lists the image in the retrieval results. Therefore, the system has better retrieval rate than existing systems and algorithms. One typical application of the proposed system is to help the computer understand what does the user draw or upload. It is based on the statistical distributions of tags of retrieved images, and the proposed system feeds back some candidate tags related to the query image. Such tags could be used for further retrieval to refine the result list. In addition, the system provides a friendly interactive interface with multiple queries. These queries are from different combinations of tags, a hand-drawn sketch and a natural image, and could help users search images flexibly and conveniently. The system runs on a database of 1.3 million images and could achieve a real-time retrieval speed. The results in the demonstration show excellent retrieval performance of the proposed system.