简介: |
Abstract:
The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, Web image classification and searching, and social networking. Automated annotation of digital pictures has been a highly challenging problem for computer scientists since the invention of computers. The capability of annotating pictures by computers can lead to breakthroughs in a wide range of applications. In our work, by advancing statistical modeling and optimization techniques, we can train computers about hundreds of semantic concepts using example pictures from each concept. The ALIPR (Automatic Linguistic Indexing of Pictures - Real Time) system of automatic and high-speed annotation for online pictures has been constructed. Large-collections of pictures from an Internet photo-sharing site, unrelated to the source of those pictures used in the training process have been tested. The experimental results show that a single computer processor can suggest annotation terms in real-time and with good accuracy. The ALIPR system reduces the time it takes for the users to tag the pictures. In this talk, I will also provide an overview of our ongoing image database retrieval projects, including SIMPLIcity image similarity search engine, the Story Picturing Engine, image-based security, computational aesthetics, and art and cultural imaging. Real-life demonstrations of some of the systems will be provided. This is a joint work with Jia Li of the Department of Statistics at Penn State. Biography: James Z. Wang is currently a Visiting Professor at the Robotics Institute of Carnegie Mellon University. He is also a tenured faculty at The Pennsylvania State University. He received a Summa Cum Laude Bachelor's degree in Mathematics and Computer Science from University of Minnesota, an M.S. in Mathematics and an M.S. in Computer Science, both from Stanford University, and a Ph.D. degree in Medical Information Sciences from Stanford University's Biomedical Informatics and Database groups. He has been a recipient of an NSF Career award and the endowed PNC Technologies Career Development Professorship. Research interests of his group include automatic image tagging, semantics-sensitive image retrieval, image security, biomedical informatics, computational aesthetics, story picturing, art image retrieval, and computer vision. The group has published two monographs and more than 20 journal articles. Science media including Discovery News, Scientific American, National Public Radio, and MIT Technology Review has reported his recent collaborative work ALIPR |
