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, 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.
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.
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 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.
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.
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.
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.
Ruijiang Li, Bin Li, Ke Zhang, Cheng Jin, Xiangyang Xue, Groupwise Constrained Reconstruction for Subspace Clustering, ICML 2012
Yao Lu, Wei Zhang, Cheng Jin, Xiangyang Xue, Learning Attention Map from Images, CVPR 2012
- Xisheng He, Zhe Wang, Cheng Jin, Yingbin Zheng, Xiangyang Xue, A simplified multi-class support vector machine with reduced dual optimization, Pattern Recognition Letters 2012
Cheng Jin, Chunlei Yang, Integrating Hierarchical Feature Selection and Classifier Training for Multi-Label Image Annotation, ACM SIGIR 2011
Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, Xingquan Zhu, Tracking User- Preference Varying Speed in Collaborative Filtering, AAAI 2011
Yuejie Zhang, Lei Cen, Cheng Jin, Xiangyang Xue and Jianping Fan, Learning Inter-Related Statistical Query Translation Models for English-Chinese Bi-Directional CLIR, IJCAI 2011
Yuejie Zhang, Lei Cen, Wei Wu, Cheng Jin and Xiangyang Xue, Fusion of Multiple Features and Supervised Learning for Chinese OOV Term Detection and POS Guessing, IJCAI 2011
Yiyang Gu, Cheng Jin, Xiangyang Xue, Quick matting: A matting method based on pixel spread and propagation, ICIP 2010
Yuejie Zhang, Lei Cen, Cheng Jin, Xiangyang Xue and Ning Zhou, Bilingual Query Translation and Expansion for Supporting More Effective Cross-Language Image Retrieval, ACM Multimedia 2010
Renzhong Wei, Hong Lu, Yingbin Zheng, Lei Cen, Cheng Jin, Xiangyang Xue, Weiguo Wu, How Context Helps: A Discriminative Codeword Selection Method for Object Detection, ICIP 2010
Jian-Feng Chen, Hong Lu, Renzhong Wei, Cheng Jin, Xiangyang Xue, An effective method for video genre classification, CIVR 2010