MindFinder: Image Search by Interactive Sketching and Tagging
- Changhu Wang ,
- Lei Zhang ,
- Zhiwei Li (李志伟)
WWW'10: 19th International World Wide Web Conference, 2010. |
In this technical demonstration, we showcase theMindFinder system − a novel image search engine. Different from ex- isting interactive image search engines, most of which only provide image-level relevance feedback, MindFinder enables users to sketch and tag query images at object level. By con- sidering the image database as a huge repository, MindFinder is able to help users present and refine their initial thoughts in their mind, and finally turn thoughts to a beautiful im- age(s). Multiple actions are enabled for users to flexibly de- sign their queries in a bilateral interactive manner by lever- aging the whole image database, including tagging, refining query by dragging and dropping objects from search results, as well as editing objects. After each action, the search re- sults will be updated in real time to provide users up-to-date materials to further formulate the query. By the deliberate but easy design of the query, MindFinder not only tries to enable users to present on the query panel whatever they are imagining, but also returns to users the most similar images to the picture in users’ mind. By scaling up the im- age database to 10 million, MindFinder has the potential to reveal whatever in users’ mind, that is where the name MindFinder comes from.
MindFinder: Finding Images by Sketching

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Sketch-based image search is a well-known and difficult problem, in which little progress has been made in the past decade in developing a large-scale and practical sketch-based search engine. We have revisited this problem and developed a scalable solution to sketch-based image search. The MindFinder system has been built by indexing more than 1.5 billion web images to enable efficient sketch-based image retrieval, and many creative applications can be expected to advance the state of the art.