In general, the goal of computer vision is to develop the algorithms and representations that will allow a computer to autonomously analyze visual information. We are especially interested in learning and recognizing visual object categories, and scalable methods for content-based retrieval and visual search.

Large amounts of interconnected visual data (images, videos) are readily available---but we don't yet have the tools to easily access and analyze them. Our group's research aims to remove this disparity, and transform how we retrieve and evaluate visual information. This requires robust methods to recognize objects, actions, and scenes, and to automatically organize and search images and videos based on their content. Key research issues that we are exploring are scalable search for meaningful similarity metrics, unsupervised visual discovery, and cooperative learning between machine and human vision systems.

     [Expand to show all 32][Minimize]