Kristen L Grauman
Professor
"Department of Computer Science "
University of Texas at Austin
United States of America
Biography
His research interests are in computer vision and machine learning. In general, the goal of computer vision is to develop the algorithms and representations that will allow a computer to autonomously analyze visual information. He 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. My 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."
Research Interest
"Computer vision and machine learning, and their applications to information retrieval; Object recognition, image search, large-scale retrieval, visual discovery, active learning."
Publications
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Grauman K (2010) Object-Graphs for Context-Aware Category Discovery. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
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Grauman K (2010) Cost-Sensitive Active Visual Category Learning.International Journal of Computer Vision (IJCV) 91.