My E-mail Address:  Hanzi.Wang@ieee.org

(From August 2008, I moved to the University of Adelaide in Australia. New link is here)

About Me:

Hanzi Wang is currently a senior research fellow in the department of computer science, the University of Adelaide, Australia.  He was an assistant research scientist (2007-2008) and a postdoctor (2006-2007)  at the Johns Hopkins University, and a research fellow at Monash University, Australia (2004-2006). He received the Ph.D degree in Computer Vision from Monash University. He has been awarded the Douglas Lampard Electrical Engineering Reseach Prize and Medal for the best PhD thesis in the Department. His research interests are concentrated on computer vision and pattern recognition including visual tracking, robust statistics, video segmentation, model fitting, optical flow calculation, fundamental matrix, image segmentation and related fields.  He is a senior member of the IEEE and he was listed in Who's Who in Science and Engineering and Who's Who in the World.

Video Demos:

• We propose a SMOG-based similarity measure. It captures both the color and the spatial layout information, and thus is more discriminative than the general color histogram based similarity measure. (See our ECCV'06 paper)

Research Projects:

• Feature Detection, Matching, and Tracking
• Motion Estimation
• Structure from Motion
• Registration of Video Data and 3D Data
• Image Registration
• Probabilistic Multiple Cue Fusion
• Effective Appearance Model and Similarity Measure for Tracking
• Tracking and Segmenting Human Body with Occlusions
• Background Initialization
• Background Modeling
• Robust Parametric Model Estimation and Its Application to Computer Vision
• Robust Optical Flow Calculation and Motion Estimation
• Image Segmentation (Range Image Segmentation and Color Image Segmentation)
• Robust Fundamental Matrix Estimation

Academic Journals:

• H. Wang, D. Mirota and G. Hager

A Generalized Kernel Consensus Based Robust Estimator.
IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI)
[Accepted]
(pdf)
 
• C. Shen, J. Kim and H. Wang

Generalized Kernel-based Visual Tracking.
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2010
[Accepted]
(pdf)
 
• X. Li, W. Hu, Z. Zhang and H. Wang

Heat Kernel Based Local Binary Pattern for Face Representation and Classification.
IEEE Signal Processing Letters (SPL)
[Conditionally Accepted]
 
• K. Schindler, D. Suter, and H. Wang

A Model-selection Framework for Multibody Structure-and-Motion of Image Sequences.
International Journal of Computer Vision (IJCV), 2008.
(pdf)
 
• H. Wang, D. Mirota, M. Ishii and G. Hager.

Anatomical Reconstruction from Endoscopic Images: Progress and Prognosis of Quantitative Endoscopy.
American Journal of Rhinology (AJR),  Vol 22, No. 1, pages 47-51, January-February 2008.
 
• H. Wang, David Suter, Konrad Schindler and Chunhua Shen

Adaptive Object Tracking Based on an Effective Appearance Filter.
IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol 29, No. 9, pages 1661-1667, 2007.
[Featured article from the September issue 2007]
(Early version appeared in ECCV'06)
(pdf)
 
• H. Wang and D. Suter.

A Consensus-Based Method for Tracking: Modelling Background Scenario and Foreground Appearance.
Pattern Recognition (PR), Vol. 40, No.3, pages 1091-1105, 2007.
(pdf), (abstract)
 
• H. Wang and D. Suter.

Robust Adaptive-Scale Parametric Model Estimation for Computer Vision.
IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), Vol. 26, No.11, pages 1459-1474, 2004.
(pdf), (abstract)
 
• H. Wang and D. Suter.

MDPE: A Very Robust Estimator for Model Fitting and Range Image Segmentation.
International Journal of Computer Vision (IJCV), Vol. 59, No.2, pages 139-166, 2004.
(pdf), (abstract)
 
• H. Wang and D. Suter.

Using Symmetry in Robust Model Fitting.
Pattern Recognition Letters (PRL), Vol. 24, No.16, pages 2953-2966, 2003.
(pdf), (abstract), (URL)
 
• B. Chen, H. Wang, H. Wei, Y. Guo , L. Guo.

Design of fully continuous phase plates for beam smoothing.
ACTA OPTICA SINICA, Vol. 21, No.4, pages 480-484, 2001.
 
• B. Chen, H. Xiao, X. Wu, H. Wang, L. Guo.

Projection Stereo-display by Using Retroreflector.
Guangdianzi Jiguang/Journal of Optoelectronics Laser, Vol. 9, pages 96-98, 1998.

• D. Suter and H. Wang.

Robust Fitting Using Mean Shift: Applications in Computer Vision.
In M. Hubert, G. Pison, A. Struyf, and S. Van Aelst, editors, Theory and Applications of Recent Robust Methods, Statistics for Industry and Technology. Birkhauser, Basel, pages 307-318, 2004.

• T.-J. Chin, H. Wang and D. Suter

The Ordered Residual Kernel for Robust Motion Subspace Clustering
Advances of Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2009. (Acceptance rate: 23.8%)
 
• T.-J. Chin, H. Wang and D. Suter.

Robust Fitting of Multiple Structures: The Statistical Learning Approach
IEEE International Conference on Computer Vision (ICCV),  Kyoto, Japan, 2009. (Acceptance rate: 23.2%)
(pdf)
 
• D. Mirota, H. Wang, R. Taylor, M. Ishii and G. Hager.

Towards Video-based Navigation for Endoscopic Endonasal Skull Base Surgery
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), London, UK, Sept. 20-24, 2009.
(pdf) (Oral presentation, acceptance rate: 5%)
 
• K. Yu, W. Hu, X. Zhang, H. Wang and Y. Jia .

Learning Group Activity in Soccer Videos from Local Motion
LECTURE NOTES IN COMPUTER SCIENCE, Asian Conference on Computer Vision (ACCV), Xi'An, China, 2009.  (Oral - 36 out of 670).
 
• C. Yuan, X. Li, W. Hu and H. Wang

Human Action Recognition Using Pyramid Vocabulary Tree
LECTURE NOTES IN COMPUTER SCIENCE, Asian Conference on Computer Vision (ACCV), Xi'An, China, 2009.
 
• H. Wang, D. Mirota, M. Ishii and G. Hager.

Robust Motion Estimation and Structure Recovery from Endoscopic Image Sequences With an Adaptive Scale Kernel Consensus Estimator
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Alaska, U.S.A., June 24-26, 2008.
(pdf)
 
• H. Wang.

Maximum Kernel Density Estimator for Robust Fitting
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, U.S.A., pages 3385-3388, March 30-April 4, 2008 (Oral - 400 out of 2800).
(pdf)
 
• H. Wang, D. Suter and Konrad Schindler.

Effective Appearance Model and Similarity Measure for Particle Filtering and Visual Tracking
LECTURE NOTES IN COMPUTER SCIENCE, European Conference on Computer Vision (ECCV), Graz, Austria, Volume 3953, pages 606-618, May 7-13, 2006.
(pdf), (abstract) (Oral - 40 out of 900)
 
• Konrad Schindler, James U, and H. Wang.

Perspective n-view Multibody Structure-and-Motion through Model Selection.
LECTURE NOTES IN COMPUTER SCIENCE, European Conference on Computer Vision (ECCV), Graz, Austria, Volume 3951, pages 606-619,  May 7-13, 2006.
(pdf) (Oral - 40 out of 900)
 
• H. Wang and D. Suter.

Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues.
International Conference on Pattern Recognition (ICPR), Hong Kong, China, Volume 4, pages 892-895, August 20-24, 2006.
(pdf)
 
• H. Wang and D. Suter.

Background Subtraction Based on a Robust Consensus Method.
International Conference on Pattern Recognition (ICPR), Hong Kong, China, Volume 1, pages 223-226, August 20-24, 2006.
(pdf)
 
• H. Wang and D. Suter.

A Novel Robust Statistical Method for Background Initialization and Visual Surveillance.
LECTURE NOTES IN COMPUTER SCIENCE, Asian Conference on Computer Vision (ACCV), Hyderabad, India, Volume 3851, pages 328-337, January 13-16, 2006.
(pdf)
 
• K. Schindler and H. Wang.

Smooth Foreground-Background Segmentation for Video Processing.
LECTURE NOTES IN COMPUTER SCIENCE, Asian Conference on Computer Vision (ACCV), Hyderabad, India, Volume 3852, pages 581-590, January 13-16, 2006.
(pdf)
 
• H. Wang and D. Suter.

Background Initialization with A New Robust Statistical Approach.
IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS'05) in conjunction with ICCV,  Beijing, China, pages 153-159, Oct. 15-21, 2005.
 
• H. Wang and D. Suter.

Tracking and Segmenting People with Occlusions by a Sample Consensus Based Method.
IEEE International Conference on Image Processing (ICIP),  Genova, Italy, pages 410-413, Sept. 11-14, 2005.
(pdf)
 
• H. Wang and D. Suter.

A Re-Evaluation of Mixture-of-Gaussian Background Modeling.
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Pennsylvania, USA, pages 1017-1020, March 19-23, 2005.
(pdf)
 
• H. Wang and D. Suter.

Robust Fitting by Adaptive-Scale Residual Consensus.
LECTURE NOTES IN COMPUTER SCIENCE, European Conference on Computer Vision (ECCV), Prague, Czech Republic, Volume 3023, pages 107-118, May 11-14, 2004.
(pdf), (abstract)

• H. Wang and D. Suter.

False-Peaks-Avoiding Mean Shift Method for Unsupervised Peak-Valley Sliding Image Segmentation.
7th International Conference on Digital Image Computing: Techniques and Applications (DICTA'03), Sydney, pages 581-590, December 10-12, 2003.
(pdf)(Oral)
• H. Wang and D. Suter.

Color Image Segmentation Using Global Information and Local Homogeneity.
7th International Conference on Digital Image Computing: Techniques and Applications (DICTA'03), Sydney, pages 89-98, December 10-12, 2003.
(pdf)(Oral)
 
• H. Wang and D. Suter.

Variable Bandwidth QMDPE and Its Application in Robust Optic Flow Estimation.
9th IEEE International Conference on Computer Vision (ICCV), Nice, France, pages 178-183, October 2003.
(pdf), (abstract)
 
• H. Wang and D. Suter.

A Model-Based Range Image Segmentation Algorithm Using a Novel Robust Estimator.
3rd Int'l Workshop on Statistical and Computational Theories of Vision (in conjunction with ICCV'03), Nice, France, October 2003.
(pdf)
 
• D. Suter, P. Chen, and H. Wang.

Extracting Motion from Images: Robust Optic Flow and Structure from Motion.
In Proceedings Australia-Japan Advanced Workshop on Compter Vision, Sept. 9-11, 2003, Adelaide, Australia, pages 64-69, 2003.
 
• H. Wang and D. Suter.

A Novel Robust Method for Large Numbers of Gross Errors.
7th Int. Conf. on Automation, Robotics and Computer Vision (ICARCV02), Singapore, pages 326-331, December 3-6, 2002.
(pdf)(Oral)
 
• H. Wang and D. Suter.

LTSD: A Highly Efficient Symmetry-based Robust Estimator.
7th Int. Conf. on Automation, Robotics and Computer Vision (ICARCV02), Singapore, pages 332-337, December 3-6, 2002.
(pdf)(Oral)

Professional Service:

Some Useful Links:

• The Computer Vision Homepage
• CVOnline - Compendium of Computer Vision
• Computer Vision Glossary
• Baltimore Weather