Columbia University, USA
Peter N. Belhumeur is currently a Professor in the Department of Computer Science at Columbia University and the Director of the Laboratory for the Study of Visual Appearance (VAP LAB). He received a Sc.B. in Information Sciences from Brown University in 1985.
He received his Ph.D. in Engineering Sciences from Harvard University under the direction of David Mumford in 1993. He was a postdoctoral fellow at the University of Cambridge's Isaac Newton Institute for Mathematical Sciences in 1994. He was made Assistant, Associate and Professor of Electrical Engineering at Yale University in 1994, 1998, and 2001, respectively. He joined Columbia University as a Professor of Computer Science in 2002.
His research focus lies somewhere in the mix of computer vision, computer graphics, and computational photography. He is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and the National Science Foundation Career Award. He won both the Siemens Best Paper Award at the IEEE Conference on Computer Vision and Pattern Recognition and the Olympus Prize at the European Conference of Computer Vision.
Title: Describable Visual Attributes for Computer Vision
Many recent advances in computer vision borrow from the field of taxonomy and its centuries-old technique for describing and classifying organisms. New computer vision methods have been developed for automatically labeling objects within images with a wide range of describable visual attributes. These visual attributes can then be used for numerous applications such as identification, image search, and photo editing. This talk will discuss the advantages (and disadvantages) of visual attributes and their success in real-world domains. In addition, this talk will present new work in discovering a dictionary of part-based attributors which focus on possibly unnameable visual attributes at object part locations. We demonstrate the usefulness of these attributors with new state-of-the-art results on verifying the identity of human faces in uncontrolled settings, identifying bird species in natural images, and determining dog breeds in iPhone photographs.
Session Chair: Subhasis Chaudhuri, IIT Bombay, India