My current research interests are Image/Video Analysis and Human-Computer Interaction. The research group I led is now carrying out projects on Image/Video Matting, Image/Video Annotation, Image Retrieval via Sketch, TV Search, TV Program Classification and Detection, and User Behavior Analysis. We also explore Android/iOS Systems and Applications to make better human-computer interaction.  My recent publications are listed in the end of this page.

Image/Video Matting

Matting is one of the key techniques in many applications, which aims at accurately estimate foreground objects in image or video. Our research focuses on how we can do it effectively and efficiently. This work was done by Yiyang Gu and Huating Zhao.

Image Enhancement using High Dynamic Range Technology

We developed our HDR algorithm to calculate the amount of light in a given scene and uses that information to preserve details within the image, even in scenes with large variations in brightness, for more realistic looking images. This work was done by Shiqian Tao and Fan Zhang.

Image Deblur

Blurred images can be found in many applications. How to deblur an image is a long studied issue. We focus on document image deblur algorithms. This work was done by Yanfei Wang and Wenjie Li.

Image Super-Resolution

Image Super-Resolution aims to enhance the resolution of an imaging system. This work was done by Jing Wang and Hao Ren.

Image Retrieval via Sketch

Images can be searched in many ways. Using sketch as search input enables users to search freely as they draw. We also provide an online version of the program, which can be accessed here. This work was done by Zheming Wang and Jianwei Yuan.

Image/Video Annotation

Automatic Image/Video Annotation helps computer to understand what we, as human beings, see the world. Robust annotation algorithms can be used in many applications such as photo album organization, robots, image/video retrieval and etc.

TV Search

TV has been the center of family entertainment for several decades. With the development of mobile devices and internet video sites, TV seems to be driven away from our sight. However, we believe with better interaction tools and search technologies, TV, as a unique big sharing screen for a whole family, is still not replaceable. We are collaborating with many leading companies in this industry to give TV a better future. This work was majorly done by batch of 2010 graduate students, led by Yiyang Gu and Yiqun Wu.

TV Program Classification and Detection

In order to gain better understanding of video sequences, it’s a challenging work to automatically  classify video clips. Currently we are working on Advertisement Detection using classification algorithms. This work was majorly done by batch of 2010 graduate students, led by Huagui Zhang and Quanping Liu.

User Behavior Analysis

User behavior gives information on how people think of the product and what we can do to improve it. It’s vital to many user-centered applications. User behavior is not a static character. We are among the first batch of researchers who discovered the changing property of user behavior. This work was done by Ruijiang Li.

Android/iOS Systems and Applications

Android and iOS are definitely overwhelming in mobile platforms. We focus on deep understanding of Android OS as well as application development on both Android and iOS. This work was majorly done by batch of 2010 graduate students, led by Yiqun Wu and Xuejun Liu.

Recent Publications (Selected):












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