Images/video convey very rich information that is embedded in the non-structured and low-level visual contents. A big challenge is the gap between the semantic concepts and the visual contents, which makes it very difficult for computers to perform efficient management of visual data and to perform semantic information retrieval. Therefore, to facilitate effective and efficient management and access of a large volume of multimedia data, video content needs to be analyzed and interpreted, the large uncertainty within the visual appearances needs to be captured and learnt from data, and the video data need to be organized for efficient retrieval. Our research involves the following topics:

• Discovering visual patterns
• Object detection in images/video
• Transductive learning for retrieving and mining visual contents
• Video data mining

The results of this project will lead to significant improvement on the quality of content-based and object-level multimedia retrieval, will greatly benefit visual recognition that requires large datasets for training and evaluation, will significantly reduce the efforts of training brand new models for un-trained scenarios, and will be very useful in intelligent video surveillance applications thus having a great impact on homeland security.

Book Chapters

1. Qi Tian, Ying Wu, Jerry Yu and Thomas S. Huang, "Self-Supervised Learning Based on Discriminative Nonlinear Features and Its application for Image Retrieval", in Managing Multimedia Semantics, edited by Uma Srinivasan and Surya Nepal, ICT Centre CSIRO, Australia, by Idea Group, Inc., 2004.

1. Ying Wu and Ting Yu, "A Field Model for Human Detection and Tracking", IEEE Trans. on Pattern Analysi s and Machine Intelligence, Vol.28, No.5., pp.753-765, May, 2006.    [PDF]
 
2. Zhimin Fan, Jie Zhou and Ying Wu, "Inference of Multiple Subspaces from High Dimensional Data Using Oriented-Frames with Application to Multibody Grouping", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.28, No.1, pp.90-105, Jan., 2006.   [PDF]
 
3. Gang Hua and Ying Wu, "Variational Maximum a Posteriori by Annealed Mean Field Analysis", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.27, No.11, pp.1747-1781, Nov., 2005.   [PDF]
 
4. Gang Hua and Ying Wu, "Sequential Mean Field Variational Analysis of Structured Deformable Shapes", Computer Vision and Image Understanding, Vol.101, No.2., pp.87-99, Feb., 2006.   [PDF]
 
5. Ying Wu and Thomas S. Huang, "Robust Visual Tracking by Integrating Multiple Cues Based on Co-Inference Learning", Int'l Journal Computer Vision, vol.58, No.1, June, 2004.  [PDF]
 
6. Qi Tian, Ying Wu, Jerry Yu and Thomas S. Huang, "Self-Supervised Learning Based on Discriminative Nonlinear Features and Its Applications for Pattern Classification", Pattern Recognition, Vol.38, No.6, 2005.  [PDF]
 
7. Ying Wu and Thomas S. Huang, "Towards Self-Exploring Discriminating Features for Visual Learning", Journal of Engineering Application on Artificial Intelligence, Vol.15, pp.139-150,2002.  [PDF]

1. Junsong Yuan and Ying Wu, "Spatial Random Partition for Common Visual Pattern Discovery", in Proc. IEEE Int'l Conf. on Computer Vision (ICCV'07), Rio de Janeiro, Brazil, Oct. 2007   [PDF]
 
2. Shengyang Dai, Ming Yang, Ying Wu and Aggelos Katsaggelos, "Detector Ensemble", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'07), Minneapolis, MN, June 2007   [PDF]
 
3. Junsong Yuan, Ying Wu and Ming Yang, "Discovery of Collocation patterns: from Visual Words to Visual Phrases", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'07), Minneapolis, MN, June 2007   [PDF]
 
4. Junsong Yuan, Ming Yang and Ying Wu, "From Frequent Itemsets To Semantically Meaningful Visual Patterns", in Proc. ACM Int'l Conf. on Knowledge Discovery and Data Mining (SIGKDD'07), San Jose, CA, August 2007   [PDF]
 
5. Junsong Yuan, Wei Wang, Jingjing Meng, Dongge Li and Ying Wu, "Mining Repetitive Clips through Finding Continuous Paths", in Proc. ACM Multimedia (ACMMM'07), Augsburg, Germany, Sept. 2007   [PDF]
 
6. Junsong Yuan, Zhu Li, Yun Fu, Ying Wu and Thomas S. Huang, "Common Spatial Pattern Discovery by Efficient Candidate Pruning", in Proc. IEEE Int'l Conf. on Image Processing (ICIP'07), San Antonio, TX, Sept. 2007   [PDF]
 
7. Fan Jiang, Ying Wu and Aggelos K. Katsaggelos, "Abnormal Event Detection From Surveillance Video By Dynamic Hierarchical Clustering", in Proc. IEEE Int'l Conf. on Image Processing (ICIP'07), San Antonio, TX, Sept. 2007   [PDF]
 
8. Ming Yang, Ying Wu and Shihong Lao, "Intelligent Collaborative Tracking by Mining Auxiliary Objects", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 06), New York City, NY, June 17-22, 2006.   [PDF]
 
9. Zhimin Fan, Ming Yang, Ying Wu, Gang Hua and Ting Yu, "Efficient Optimal Kernel Placement for Reliable Visual Tracking", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 06), New York City, NY, June 17-22, 2006.   [PDF]
 
10. Gang Hua, Ying Wu and Zhimin Fan, "Measurement Integration Under Inconsistency for Robust Tracking", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 06), New York City, NY, June 17-22, 2006.   [PDF]
 
11. Zhimin Fan and Ying Wu, "Multiple Collaborative Kernel Tracking", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, June 20-26, 2005.   [PDF]
 
12. Ying Wu, Ting Yu and Gang Hua, "A Statistical Field Model for Pedestrian Detection", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, June 20-26, 2005.   [PDF]
 
13. Ming Yang and Ying Wu, "Tracking non-stationary appearances and dynamic feature selection", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, June 20-26, 2005.   [PDF]
 
14. Ting Yu and Ying Wu, "Decentralized Multiple Target Tracking using Netted Collaborative Autonomous Trackers", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, June 20-26, 2005.  [PDF]
 
15. Ting Yu and Ying Wu, "Collaborative Tracking of Multiple Targets", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'04), vol.I, pp. 834-841, Washington, DC, June, 2004.   [PDF]
 
16. Gang Hua and Ying Wu, "Multi-scale Visual Tracking by Sequential Belief Propagation", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'04), vol.I, pp. 826-833, Washington, DC, June, 2004.   [PDF]
 
17. Zhimin Fan, Jie Zhou and Ying Wu, "Inference of Multiple Subspaces from High-Dimensional Data and Application to Multibody Grouping", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'04), vol.II, pp. 661-666, Washington, DC, June, 2004.   [PDF]
 
18. Zhimin Fan, Jie Zhou and Ying Wu, "Multibody Motion Segmentation Based on Simulated Annealing", in Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'04), vol.I, pp. 776-781, Washington, DC, June, 2004.  [PDF]
 
19. Gang Hua, Ying Wu and Ting Yu, "Analyzing Structured Deformable Shapes Via Mean Field Monte Carlo", in Proc. IEEE Asia Conference on Computer Vision ( ACCV'2004), Jeju Island, Korea, Jan., 2004.  [PDF]
 
20. Qi Tian and Jerry Yu and Ying Wu and Thomas S. Huang, "Learning Based on Kernel Discriminant-EM Algorithm for Image Classification",  in Proc. IEEE International Conferenece On Acoustics, Speech, and Signal Processing (ICASSP'04), Montreal, Canada, 2004.  [PDF]
 
21. Ying Wu, Gang Hua and Ting Yu, "Tracking Articulated Body by Dynamic Markov Network", in Proc. IEEE Int'l Conf. on Computer Vision (ICCV'03), pp.1094-1101, Nice, France, Oct., 2003.  [PDF]

1. Shengyang Dai, Ming Yang and Ying Wu, "Detector Ensemble", Technical Report, EECS Dept., Northwestern University, 2005.  [PDF]
 
2. Junsong Yuan and Ying Wu, "Muti-level Discovery of Spatial Co-location Visual Patterns", Technical Report, EECS Dept., Northwestern University, 2005.  [PDF]