UNC Chapel Hill’s Alex Berg presents “Expanding Vision and Seeing Its Limits” as part of the IRIM Robotics Seminar Series. The event will be held in the TSRB Banquet Hall from 12-1 p.m. and is open to the public.
The presentation will have two parts. First, recognition techniques in computer vision are beginning to work, making the next question, “What should we recognize?” I will present some work on increasing the label space for recognition toward large numbers of semantic labels embedded in a hierarchy, toward multiple attribute labels, and toward detailed spatial parsing. Predictions of these labels are improving results on problems from face recognition to large-scale similar image retrieval and building stronger connections between computer vision and natural language processing. The second part of the presentation will attempt to sketch out places were vision is failing to address the needs of application areas, including robotics.
Alex Berg is an assistant professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. His research concerns computational visual recognition. Berg has worked on general object recognition in images, action recognition in video, human pose identification in images, image parsing, face recognition, image search, and machine learning for computer vision. He co-organizes the ImageNet Large Scale Visual Recognition Challenge, and has co-organized a series of workshops on large scale recognition in computer vision.
Before joining the Department of Computer Science in 2013, Berg was on the faculty at Stony Brook University, served as a research scientist at Columbia University, and was a research scientist at Yahoo! Research. While earning his Ph.D. at the University of California, Berkeley, he developed a novel approach to deformable template matching. Berg earned a B.A. and M.A. in mathematics from Johns Hopkins University and learned to race sailboats at the Severn Sailing Association in Annapolis.