Visual Image Browser

VisualImageBrowser.pngThe integration of intelligent image content analysis and interactive visualization has produced a complete visual analytics tool. Image content analysis is automatically applied to a set of images with unknown content. Concepts within the images can be found from a pre-trained set or added by user selection on a training set of images. Images are then clustered according to their properties and according to the concepts they contain so that like images will be close to one another. The figure shows over 1000 images organized in this way. The user can then explore the image collection applying several highly interactive tools such as search to find all images similar to an example image, search to find dissimilar or un-clustered images (i.e., where no concepts are found), and exploration of the concept space itself. The latter provides a means to scale up to tens of thousands of images or more using pixel-based techniques. This work is led by Jianping Fan and Jing Yang.