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Hashing for Large-Scale Visual Search

2014-07-12来源: 浏览次数:


Speaker: Wei Liu (刘威)

      Affiliation: IBM T. J. Watson Research

                         Center, NY, USA

     Time: 201471715:00

      Location: 主楼II241

Abstract:
Designing effective and efficient indexing schemes and search algorithms has recently attracted considerable attention due to the explosive growth of data, such as Web documents, images, and consumer videos on the Internet. Since exact nearest neighbor search is infeasible for large-scale multimedia applications which require exhaustive data scanning and huge memory overhead, hashing based approximate nearest neighbor (ANN) search has become popular owing to its practical efficiencies in both storage and search. Recently, tremendous efforts have been paid to design more efficient and semantics-aware hashing techniques though incorporating various machine learning tools and algorithms to yield compact binary codes, which are named learning to hash in literature.

In this talk, we provide a comprehensive survey of the recent developments of learning to hash in both methodologies and applications, ranging from unsupervised to supervised approaches. In particular, we compare the motivations, objectives, and solutions of popular learning-based hashing methods and also discuss the pros and cons. Finally, we will discuss the future directions and trends of hashing being applied to large-scale multimedia search.

Biography:

Dr. Wei Liu received the M.Phil. and Ph.D. degrees in electrical engineering from Columbia University, New York, NY, USA in 2012. Currently, he is a research staff member of IBM T. J. Watson Research Center, Yorktown Heights, NY, USA. His research interests include machine learning, data mining, computer vision, pattern recognition, multimedia, and information retrieval. Dr. Liu has published over 60 papers in peer-reviewed journals and conferences such as Proceedings of IEEE, IEEE Transactions on Image Processing, ICML, KDD, CVPR, ICCV, ECCV, MICCAI, ACM Multimedia, IJCAI, AAAI, SIGIR, SIGCHI, etc. His recent paper wins the best paper travel award for ISBI 2014.Dr. Wei Liu received the M.Phil. and Ph.D. degrees in electrical engineering from Columbia University, New York, NY, USA in 2012. Currently, he is a research staff member of IBM T. J. Watson Research Center, Yorktown Heights, NY, USA. His research interests include machine learning, data mining, computer vision, pattern recognition, multimedia, and information retrieval. Dr. Liu has published over 60 papers in peer-reviewed journals and conferences such as Proceedings of IEEE, IEEE Transactions on Image Processing, ICML, KDD, CVPR, ICCV, ECCV, MICCAI, ACM Multimedia, IJCAI, AAAI, SIGIR, SIGCHI, etc. His recent paper wins the best paper travel award for ISBI 2014.

主办单位: 西安电子科技大学影像处理系统实验室
西安电子科技大学国际交流与合作处

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