2015年6月17日，美国德克萨斯大学圣安东尼奥分校Qi Tian教授应电子工程与信息科学系和多媒体计算与通信-教育部微软重点实验室的邀请在科大西区科技实验楼西楼1213会议室做题为《Discriminative Visual Representations for Image Search and Classification》的高水平学术前沿讲座。该讲座中，Qi Tian教授深入系统地介绍了图像检索的历史、发展和前沿，并着重介绍了其研究组近年来在大规模图像检索和图像分类方面取得的研究成果，并与参会师生进行了升入的交流和探讨。Qi Tian教授与我系老师长期紧密合作，联合培养了多名优秀学生，发表了一批高水平的科研论文。

图1 报告人：Professor Qi Tian (University of Texas at San Antonio, USA)

　　图2 Qi Tian教授做题为《Discriminative Visual Representations for Image Search and Classification》的报告。

　　报告摘要：The emergence of massive image data has urged effective and efficient techniques towards large-scale image search and classification. Generally, the introduction of local invariant features and the Bag-of-Words model has witnessed the development of both research fields. However, this model suffers from both the information loss during vector quantization and the deficiency in the descriptive power of various aspects of images. In the light of this problem, this talk will present several recent works in our group that focus on the discriminative representations in image search and classification.  To be specific, I will first describe feature representations such as binary descriptors, region/part descriptors including CNN, as well as informative quantization. Then, in accordance to the descriptors, I will introduce a series of recently proposed indexing schemes aiming at reducing both memory and time cost, such as cross-index, cascade category-aware index, tensor-index, super-image index, etc. Third, I will present some exciting advances in discriminative feature fusion strategies, such as coupled multi-index, bayes merging, co-index, etc. Moreover, our recent works on post-processing such as ImageWeb, query-adaptive fusion will also be discussed. Last but not least, I will summarize our achievements in advancing the state-of-the-arts on benchmark datasets in image search and classification.

　　报告人简介：Qi Tian is currently a Full Professor in the Department of Computer Science, the University of Texas at San Antonio (UTSA). During 2008-2009, he took one-year Faculty Leave at Microsoft Research Asia (MSRA) in the Media Computing Group. He received his Ph.D. in ECE from University of Illinois at Urbana-Champaign (UIUC) in 2002 and his B.E and M.S degrees from Tsinghua University and Drexel University in 1992 and 1996, respectively, all from electronic engineering. Dr. Tian’s research interests focus on multimedia information retrieval and computer vision and published over 290 refereed journal and conference papers. He received the Best Paper Award in PCM 2013, ACM ICIMCS 2012 and MMM 2013, a Top 10% Paper Award in MMSP 2011, the Student Contest Paper Award in ICASSP 2006. His research projects are funded by NSF, ARO, DHS, Google, FXPAL, NEC, SALSI, CIAS, Akiira Media Systems, HP and UTSA. He received 2010 ACM Service Award. 

　　Dr. Tian is the Associate Editor of IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and in the Editorial Board of Journal of Multimedia (JMM) and Journal of Machine Vision and Applications (MVA), he is also the Guest Editors of IEEE Transactions on Multimedia, Journal of Computer Vision and Image Understanding, etc.