Shengping Zhang, PhD


Associate Professor
School of Computer Science and Technology
Harbin Institute of Technology
2 Cultural West
Huancui, Weihai, Shandong, China

Biography

Dr. Zhang is an Associate Professor in the School of Computer Science and Technology at Harbin Institute of Technology, China. He is also a Postdoctoral Research Fellow at Hong Kong Baptist University, supported by Hong Kong Scholars Program. Dr. Zhang is the Young Excellent Talent of the Harbin Institute of Technology.

Research Interest

His research interests include: Computational neuroscience, Computer vision and machine learning, especially for moving object detection, tracking and action recognition.

Scientific Activities

• (2013-Present) Associate Editor, Signal, Image and Video Processing
• (2013-Present) Editorial Board Member, Journal of Postdoctoral Research, Journal of Computer science
• (2014) Lead Guest Editor, IET Computer Vision
• (2013) Lead Guest Editor, Signal, Image and Video Processing
• (2013)Program Committee, The 8th Chinese Conference on Biometric Recognition
• (2014) Session Chair, The 3th International Joint Workshop on Information Science, Technology and Application

Publications

1. Zhang S, Yao H, Sun X, et al. Action recognition based on overcomplete independent component analysis. Information sciences. 2014; 281: 635-647. doi: 10.1016/j.ins.2013.12.052
2. Zhang S, Zhou H, Zhang B, Han Z, Guo Y. Signal, image and video processing special issue: Semantic representations for social behavior analysis in video surveillance systems. Signal Image and Video Processing. 2014; 8(1): 73-74. doi: 10.1007/s11760-014-0721-9
3. Zeng L, Zhang S, Zhang J, Zhang Y. Dynamic image mosaic via SIFT and dynamic programming. Machine Vision and Applications. 2014; 25(5): 1271-1282. doi: 10.1007/s00138-013-0551-8
4. Zeng L, Zang W, Zhang S, Wang D. Video Image Mosaic Implement Based on Planar-Mirror-Based Catadioptric System. Signal Image and Video Processing. 2014; 8(6): 1007-1014. doi: 10.1007/s11760-012-0413-2
5. Zhang Y, Zhang S, Huang Q, Serre T. Learning Sparse Prototypes for Crowd Perception via Ensemble Coding Mechanisms. ECCV 2014 5th International Workshop on Human Behavior Understanding (HBU 2014) . 2014; 86-100. doi: 10.1007/978-3-319-11839-0_8
6. Zhang S, Yao H, Sun X, Lu X. Sparse Coding Based Visual Tracking: Review and Experimental Comparison. Pattern Recognition. 2013; 46(7): 1772-1788. doi: 10.1016/j.patcog.2012.10.006
7. Zhang S, Yao H, Zhou H, Sun X, Liu S. Robust Visual Tracking Based on Online Learning Sparse Representation. Neurocomputing. 2013; 100(1): 31-40. doi: 10.1016/j.neucom.2011.11.031
8. Tang X, Zhang S, Yao H. Sparse Coding Based Motion Attention for Abnormal Event Detection. International Conference on Image Processing (ICIP 2013). 2013; 3602-3606. doi: 10.1109/ICIP.2013.6738743
9. Sun X, Yao H, Zhang S, Sun M. Non-girid Object Tracking by Adaptive Data-Driven Kernel. International Conference on Image Processing (ICIP 2013) . 2013; 2958-2962. doi: 10.1109/ICIP.2013.6738609
10. Jiang X, Yao H, Zhang S, Lu X, Zeng W. Night Video Enhancement Using Improved Dark Channel Prior. International Conference on Image Processing (ICIP 2013). 2013; 553-557. doi: 10.1109/ICIP.2013.6738114
11. Zhang S, Yao H, Sun X, Liu S. Robust Visual Tracking Using An Effective Appearance Model Based on Sparse Coding. ACM Transactions on Intelligent Systems and Technology. 2012; 3(3): 43. doi: 10.1145/2168752.2168757
12. Sun X, Yao H, Zhang S. A Novel Supervised Level Set Method for Non-Rigid Object Tracking. International Conference on Computer Vision and Pattern Recognition (CVPR 2011). 2011; 3393-3400. doi: 10.1109/CVPR.2011.5995656
13. Zhang B, Zhang S, Liu J. Sparse Regression Analysis for Object Recognition. International Conference on Image Processing (ICIP 2011). 2011; 2381-2384. doi: 10.1109/ICIP.2011.6116121
14. Sun X, Yao H, Zhang S. Contour Tracking Via On-line Discriminative Appearance Modeling Based Level Sets. International Conference on Image Processing (ICIP 2011). 2011; 2317-2320.
15. Sun Z, Yao H, Zhang S, Sun X. Robust Visual Tracking via Context Objects Computing. International Conference on Image Processing (ICIP 2011). 2011; 509-512. doi: 10.1109/ICIP.2011.6116564
16. Sun X, Yao H, Zhang S. Robust Object Tracking via Inertial Potential based Mean Shift. International Conference on Internet Multimedia Computing and Service (ICIMCS 2011). 2011; 178-181. doi: 10.1145/2043674.2043725
17. Zhang S, Yao H, Liu S. Robust visual tracking using feature-based visual attention. International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010). 2010; 1150- 1153. doi: 10.1109/ICASSP.2010.5495369
18. Zhang S, Yao H, Sun X, Liu S. Robust object tracking based on sparse representation. International Conference on Visual Communications and Image Processing (VCIP 2010). 2010; 77441N-77441N-8.
19. Zhang S, Yao H, Liu S. Partial occlusion robust object tracking using an effective appearance model. International Conference on Visual Communications and Image Processing (VCIP 2010). 2010; 77442U-77442U-8.
20. Zhang S, Yao H, Gao P. Robust Object Tracking Combining Color and Scale Invariant Features˘A˙I. International Conference on Visual Communications and Image Processing (VCIP 2010). 2010; 77442R-77442R-8. doi: 10.1117/12.863844
21. Zhang S, Wu J, Tian Y, Liu S, Sun X. Robust Visual Tracking Based on Occlusion Detection and Particle Redistribution. International Conference on Internet Multimedia Computing and Service (ICIMCS 2010). 2010; 159-162. doi: 10.1145/1937728.1937766
22. Xu Z, Zhang S, Pan J, Sun X, Liu S. Robust visual tracking combining global and local appearance models. International Conference on Internet Multimedia Computing and Service (ICIMCS 2010). 2010; 155-158. doi: 10.1109/TPAMI.2012.145
23. Sun X, Yao H, Zhang S. Adaptive Particle Filter Based on Energy Filed for Robust Object Tracking in Complex Scenes. Pacific-Rim Conference on Multimedia (PCM 2010). 2010; 437-448. doi: 10.1007/978-3-642-15702-8_40
24. Sun X, Yao H, Zhang S. A Refined Particle Filter Method for Contour Tracking. International Conference on Visual Communications and Image Processing (VCIP 2010). 2010; 77441M-77441M-8. doi: 10.1117/12.863450
25. Sun X, Yao H, Zhang S, Zhong B. On-Line Discriminative Appearance Modeling for Robust Object Tracking. International Conference on Pervasive Computing, Signal Processing and Applications (PCSPA 2010). 2010; 78-81. doi: 10.1109/PCSPA.2010.28
26. Liu S, Yao H, Zhang S, Gao W. A Steganography Strategy Based on Equivalence Partitions of Hiding Units. International Conference on Multimedia & Expo (ICME 2010). 2010; 1299-1304. doi: 10.1109/ICME.2010.5583275
27. Liu S, Shi F, Wang J, Zhang S, Gao W. An Improved Spatial Spread- Spectrum Video Watermarking. International Conference on Intelligent Computation Technology and Automation (ICICTA 2010). 2010; 587-590. doi: 10.1109/ICICTA.2010.721
28. Shi F, Liu S, Yao H, Liu Y, Zhang S, Gao W. Scalable and Credible Video Watermarking Towards Scalable Video Coding. Pacific-Rim Conference on Multimedia (PCM 2010). 2010; 697-708. doi: 10.1007/978-3-642-15702-8_64
29. Liu H, Zhou C, Shen J, Li P, Zhang S. Video Caption Detection Algorithm Based on Multiple Instance Learning. International Conference on Internet Computing for Science and Engineering (ICICSE 2010). 2010; 20-24. doi: 10.1109/ICICSE.2010.11
30. Zhang S, Yao H, Liu S. Spatial-temporal nonparametric background subtraction in dynamic scenes. International Conference on Multimedia & Expo (ICME 2009). 2009; 518-521. doi: 10.1109/ICME.2009.5202547
31. Zhang S, Yao H, Liu S. Dynamic Background Subtraction Based on Local Dependency Histogram. International Journal of Pattern Recognition and Artificial Intelligence. 2009; 23(7): 1397- 1419. doi: 10.1142/S0218001409007569
32. Zhang S, Yao H, Liu S, Chen X, Gao W. A Covariance-based Method for Dynamic Background Subtraction. International Conference on Pattern Recognition (ICPR 2008). 2008; 3141-3144. doi: 10.1109/ICPR.2008.4761162
33. Zhang S, Yao H, Liu S. Dynamic Background Modeling and Subtraction Using Spatio-temporal Local Binary Patterns. International Conference on Image Processing (ICIP 2008). 2008; 1556-1559. doi: 10.1109/ICIP.2008.4712065
34. Zhang S, Yao H. A novel feature-level multiple HMMs classifier for Lipreading based on Ada-Boost Gabor kernels selection. International Conference on Computer Vision, pattern Recognition and Image Processing (CVPRIP 2008). 2008; 1-6.
35. Zhang S, Yao H, Wan Y, Wang D. Combining Global and Local Classifiers for Lipreading. The Second International Conference on Affective Computing and Intelligent Intelligence (ACII 2007). 2007; 733-744. doi: 10.1007/978-3-540-74889-2_73