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Tao
MEI, Ph.D.
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Research Staff Member
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5F Sigma, 49 Zhichun Road
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Beijing 100190, P. R. China
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| Tel: | + 86 - 10 - 5896 3036 | ||
| Fax: | + 86 - 10 - 8809 7306 | ||
| Email: | |||
| Personal: | |||
| CV: | [PDF] | ||
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Bio Dr. Tao Mei received the B.E. degree in automation and the Ph.D. degree in pattern recognition and intelligent systems from the University of Science and Technology of China, Hefei, in 2001 and 2006, respectively. He joined Microsoft Research Asia, Beijing, China, as a Researcher Staff Member, in 2006. He is a visiting professor of the Xidian University during 2009-2012. His current research interests include multimedia content analysis, computer vision, and internet multimedia applications such as search, advertising, management, social network, mobile applications. He is the author of one book, six book chapters, and over 80 journal and conference papers in these areas, and holds more than 20 filed international and U.S. patents or pending applications. Dr. Mei serves as an Editorial Board Member for Journal of Multimedia (Academy) and Neurocomputing (Elsevier), a Guest Editor for IEEE Multimedia for the Special Issue on "Knowledge Discovery over Community-Contributed Multimedia Data: Opportunities and Challenges," ACM/Springer Multimedia Systems for the Special Issue on "Multimedia Intelligent Services and Technologies," and Elsevier Journal of Visual Communication and Image Representation for the Special Issue on "Large-Scale Image and Video Search: Challenges, Technologies, and Trends," a Technical Program Committee Member for numerous international conferences, and a Technical Reviewer for over 20 prestigious international journals. He was the principle designer of the automatic video search system that achieved the best performance in the worldwide TRECVID evaluation in 2007. He received the Best Paper and Best Demonstration Awards in the ACM International Conference on Multimedia 2007, the Best Poster Paper Award in the IEEE International Workshop on Multimedia Signal Processing 2008, and the Best Paper Award in the ACM International Conference on Multimedia 2009. He is a Member of the IEEE and the ACM. |
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| * New: Online Multimedia Advertising, a book to be published by IGI Global. [Updates for Preparing Book Chapters] | |||
| *Notes: I am always looking for outstanding research and development interns. If you are interested in multimedia related research and projects, please do not hesitate to send your resume to me. | |||
| Representative Publications [full list by year] [full list by categories] [DBLP] | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Visual
Query Suggestion Zheng-Jun Zha, Linjun Yang, Tao Mei, et al. ACM Multimedia, pp.15-24, 2009 Best Paper Award from SIGMM 2009 |
This paper proposes a new query suggestion scheme named Visual Query Suggestion which is dedicated to image search. It provides a more effective query interface to formulate an intent-specific query by joint text and image suggestions. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Contextual
In-Image Advertising Tao Mei, Xian-Sheng Hua, Shipeng Li ACM Multimedia, pp. 439-448, 2008. |
ImageSense is an innovative contextual advertising system driven by images, which automatically associates relevant ads with an image rather than the entire text in a Web page and seamlessly inserts the ads in the nonintrusive areas within each individual image. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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VideoSense
- Towards Effective Online Video Advertising Tao Mei, Xian-Sheng Hua, Linjun Yang, Shipeng Li ACM Multimedia, pp. 1075-1084, 2007. |
VideoSense is a novel advertising system for online video service, which automatically associates the most relevant video ads with videos and seamlessly inserts the ads at the most appropriate positions within each video. VideoSense aims to embed more contextually relevant ads at less intrusive positions within video stream. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Video
Collage: Presenting a Video Sequence Using a Single Image Tao Mei, Bo Yang, Shi-Qiang Yang, Xian-Sheng Hua The Visual Computer, 25(1): 39-51, 2009. Best Demo Award from SIGMM 2007 |
Video Collage is a kind of synthesized image that enable users to quickly browse the video content. Given a video, Video Collage is able to select the most representative images from the video, extract salient regions of interest (ROI) from these images, and seamlessly arrange ROI on a given canvas. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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When
Multimedia Advertising Meets the New Internet Era Xian-Sheng Hua, Tao Mei, Shipeng Li IEEE Workshop on Multimedia Signal Processing, 2008. Best Poster Award from MMSP 2008 |
Conventional ad-networks treat image and video advertising as general text advertising, while in MediaSense, we summarize the trends of online advertising and propose an innovative advertising model driven by the compelling contents of images and videos. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Multi-Graph-Based
Query-Independent Learning for Video Search Yuan Liu, Tao Mei, Xiuqing Wu, Xian-Sheng Hua IEEE Trans. on Circuits and Systems for Video Technology, 19(12): 1841-1850, 2009. |
We propose a novel query-independent learning approach based on multi-graph to video search, which learns the relevance information existing in the query-shot pairs. The proposed approach is more general and suitable for a real-world video search system as the learned relevance is independent on any query and any dataset. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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CrowdReranking:
Exploring Multiple Search Engines for Visual Search Reranking Yuan Liu, Tao Mei, Xian-Sheng Hua ACM SIGIR, 2009. |
CrowdReranking is a new method for visual search reranking, which is characterized by mining relevant visual patterns from image search results of multiple search engines which are available on the Internet. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Coherent
Image Annotation by Learning Semantic Distance Tao Mei, Yong Wang, Xian-Sheng Hua, Shaogang Gong, Shipeng Li IEEE CVPR, 2008. |
We propose a novel approach to image annotation which learns a Semantic Distance by capturing the prior annotation knowledge and propagates the annotation of an image as a whole entity. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Multi-Layer
Multi-Instance Learning for Video Concept Detection Zhiwei Gu, Tao Mei, Xian-Sheng Hua, et al. IEEE Trans. on Multimedia, 10(8): 1605-1616, 2008. |
Video is essentially a kind of media with multi-layer (ML) structure. We call such multi-layer structure and the "bag-instance" relations embedded in the structure as Multi-Layer Multi-Instance (MLMI) setting. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Structure
and Event Mining in Sports Video with Efficient Mosaic |
We propose a mosaic based approach to key-event as well as structure mining for sports video analysis. Mosaic is generated for each shot by a novel efficient mosaicing scheme. Based on mosaic, the structure and event in sports video are mined by the methods with prior knowledge and without prior knowledge. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Professional Activities Associate Editor | Guest Editor
Special Session Organizer
Organization Committee Member
Selected Technical Program Committee Member
Session Chairs
Reviewer
Awards
The interns I mentored at MSR Asia
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