Abstract

We introduce an interactive framework for image understanding, a game that is enjoyable and provide valuable image annotations. When people play the game, they provide useful information about contents of an image. In reality the most accurate method to describe the content of an image is manual labelling. Our approach is to motivate people to label imagers while entertaining themselves. Therefore if this game becomes popular it will be able to annotate most imagers on the web within a couple of months. When considering accuracy we use a combination of computer vision techniques to secure the accuracy of image labelling. By doing this we believe our system will make a significant contribution to address the semantic gap in the computer vision sector.

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seneviratne2008image
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