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Special Editors' Introduction to the Special Issue on Award-Winning Papers from the IEEE Conference on Computer Vision and Pattern Recognition 2010 (CVPR 2010)

Trevor Darrell, IEEE Computer Society
David Hogg, IEEE Computer Society
David Jacobs

Pages: pp. 1665-1666


About the Authors

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Trevor Darrell received the BSE degree from the University of Pennsylvania in 1988, having started his career in computer vision as an undergraduate researcher in Ruzena Bajcsy's GRASP lab. received the SM and PhD degrees from MIT in 1992 and 1996, respectively. He is on the faculty of the Computer Science Division of the Electrical Engineering and Computer Science Department at the University of Ccalifornia, Berkeley, and is the vision group lead at ICSI. His group develops algorithms to enable multimodal conversation with robots and mobile devices, and methods for object and activity recognition on such platforms. His interests include computer vision, machine learning, computer graphics, and perception-based human computer interfaces. He was previously on the faculty of the MIT Electrical Engineering and Computer Science Department from 1999-2008, where he directed the Vision Interface Group. He was a member of the research staff at Interval Research Corporation from 1996-1999. He is a member of the IEEE Computer Society.
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David Hogg received the BSc degree in applied mathematics from the University of Warwick, the MSc degree in computer science from the University of Western Ontario, and the PhD degree from the University of Sussex. He was on the faculty of the School of Cognitive and Computing Sciences at the University of Sussex from 1984 until 1990, when he was appointed a full professor of artificial intelligence at the University of Leeds, where he is now Pro-Vice-Chancellor for Research and Innovation. During 1999-2000, he was a visiting professor at the MIT Media Lab in Cambridge. He has been an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence (2006-2010) and program cochair of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. His current research is on activity analysis, dealing especially with learning and the integration of qualitative and quantitative representations. He is a fellow of the ECCAI and a member of the IEEE Computer Society.
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David W. Jacobs received the BA degree from Yale University in 1982. From 1982 to 1985, he worked for Control Data Corporation on the development of data base management systems, and attended graduate school in computer science at New York University. From 1985 to 1992, he attended MIT, where he received the MS and PhD degrees in computer science. He is a professor in the Department of Computer Science at the University of Maryland with a joint appointment in the University's Institute for Advanced Computer Studies (UMIACS). From 1992 to 2002, he was a research scientist and then a senior research scientist at the NEC Research Institute. In 1998, he spent a sabbatical at the Royal Institute of Technology (KTH) in Stockholm, and in 2008 spent a sabbatical at the Ecole Normale Supérieure de Cachan. In 2002, he joined the Computer Science Department at the University of Maryland. His research has focused on human and computer vision, especially in the areas of object recognition and perceptual organization. He has also published articles in the areas of motion understanding, memory and learning, computer graphics, human computer interaction, and computational geometry. He has served as an associate editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence, and has assisted in the organization of many workshops and conferences, including serving as program cochair for CVPR 2010. He and his coauthors received honorable mention for the best paper award at CVPR 2000. He also coauthored a paper that received the best student paper award at UIST 2003. In collaboration with researchers at Columbia University and the Smithsonian Institution he created Leafsnap, an app that uses computer vision for plant species identification, for which he and his collaborators have been awarded the 2011 Edward O. Wilson Biodiversity Technology Pioneer Award.
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