Multimedia Search and Mining (MSM) group focuses on pattern analysis and extraction for multimedia understanding, search, and data mining. We are working on research problems in search-based image annotation, large scale visual (image and video) indexing and search, sketch-based image search, object recognition with 3D structures, social multimedia analytics, etc.
- Mobile Video Search
Mobile video is quickly becoming a mass consumer phenomenon. More and more people are using their smartphones to search and browse video contents while on the move. This project is to develop an innovative instant mobile video search system through which users can discover videos by simply pointing their phones at a screen to capture a very few seconds of what they are watching.
- 3D Object Reconstruction and Recognition
We study the problem of 3D object reconstruction and recognition. For reconstruction, we aim at developing algorithms and systems to lower down the barrier of 3D reconstruction for common users. In this way, we can collect a world-class 3D object repository via leveraging crowdsourcing. For recognition, we aim at dealing with a large-scale task (e.g. identifying thousands of objects), and providing real-time performance.
- Picto: A large scale visual indexing and recognition system
In this project, we focus on developing algorithms for large-scale image indexing and recognition. Our research covers low-level image features, middle level image representations, and indexing and ranking algorithms.
- MindFinder: Finding Images by Sketching
Sketch-based image search is a well-known and difficult problem, in which little progress has been made in the past decade in developing a large-scale and practical sketch-based search engine. We have revisited this problem and developed a scalable solution to sketch-based image search. The MindFinder system has been built by indexing more than two million web images to enable efficient sketch-based image retrieval, and many creative applications can be expected to advance the state of the art.
- Mobile Multimedia Computing
Mobile devices are becoming the most frequently used terminal to access the information through the Internet and social networks. More and more multimedia content is spreading over the network of mobile devices. This area is concerned with intelligent multimedia techniques to facilitate effort-free multimedia experiences on mobile devices, including media acquisition, editing, sharing, browsing, management, search, advertising, and related user interface.
- Multimedia Advertising
The ever increasing multimedia content on the Internet has become the primary source for more effective online advertising. Conventional advertising systems treat multimedia content as the same as general text, without considering automatically monetizing the rich content of the images and videos. This research direction will leverage content analysis and understanding to enable more effective and efficient advertising on multimedia content, whether on the Internet and mobile devices.
- Video Collage
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 from these images, and seamlessly arrange ROI on a given canvas. Video Collage can be used for Windows Vista Explorer, Live Search Video, as well as MSN Soapbox.
- Yingwei Pan, Ting Yao, Tao Mei, Houqiang Li, Chong-Wah Ngo, and Yong Rui, Click-through-based Cross-view Learning for Image Search, ACM – Association for Computing Machinery, July 2014.
- tao mei, yong rui, shipeng li, and qi tian, Multimedia Search Reranking: A Literature Survey, in ACM Computing Surveys, 2014.
- Wu Liu, Tao Mei, Yongdong Zhang, Jintao Li, and Shipeng Li, Listen, Look, and Gotcha: Instant Video Search with Mobile Phones by Layered Audio-Video Indexing, ACM Multimedia, October 2013.
- Wenyuan Yin, Tao Mei, and Chang Wen Chen, Automatic Generation of Social Media Snippets for Mobile Browsing, ACM Multimedia, October 2013.
- Ting Yao, Tao Mei, Chong-Wah Ngo, and Shipeng Li, Annotation for Free: Video Tagging by Mining User Search Behavior, ACM Multimedia, October 2013.
- Ting Yao, Yuan Liu, Chong-Wah Ngo, and Tao Mei, Unified Entity Search in Social Media Community, in International World-Wide Web Conference (WWW), May 2013.
- Tao Mei, Jiebo Luo, Houqiang Li, Shipeng Li Heng Liu, Tao Mei, and Shipeng Li, Finding Perfect Rendezvous On the Go: Accurate Mobile Visual Localization and Its Applications to Routing, in ACM Multimedia, ACM Multimedia, November 2012.