MindFinder

In this technical demonstration, we showcase the MindFinder system $-$ a novel image search engine. Different from existing 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 considering 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 image(s). Multiple actions are enabled for users to flexibly design their queries in a bilateral interactive manner by leveraging 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 results 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 image database to 10 million, MindFinder has the potential to reveal whatever in users' mind, that is where the name MindFinder comes from.