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Jiayong Zhang
PhD Student

No longer a member of RI.

For more information, see my personal homepage.

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My primary interest is in the intelligence of perception. Specifically, I study computer vision, pattern recognition and machine learning, with an emphasis on statistical methods and their practical applications.

My Ph.D. thesis work involves matching articulated object models to still images. The human body is a typical example of a nonrigid, articulated object. Body localization has a 20-year history in computer vision, yet remains one of the fundamental unsolved problems. Currently I am studying this problem in a generic setting: single image, arbitrary pose, and arbitrary viewpoint.

Some other problems I have worked on include: OCR and handwriting recognition, cervical cancer diagnosis, and feature extraction/selection.

computer vision, image processing, machine learning, pattern recognition, and statistics

• Biomedical Image Analysis - We are an interdisciplinary team interested in develping algorithms for biomedical image analysis under an image feature-based machine learning framework.

• Non-Invasive Optical Imaging in vivo for Early Detection and Advanced Diagnosis of Cancer

• Body Localization in Still Images Using Hierarchical Models and Hybrid Search
  J. Zhang, J. Luo, R. Collins, and Y. Liu
  Proceedings of the 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06), Vol. II, June, 2006, pp. 1536 -- 1543. [Abstract]
  Download: pdf [981 KB] copyrighted

• Statistical Modeling and Localization of Nonrigid and Articulated Shapes
  J. Zhang
  doctoral dissertation, tech. report CMU-RI-TR-06-18, Robotics Institute, Carnegie Mellon University, March, 2006. [Abstract]
  Download: pdf [11774 KB] copyrighted

• Bayesian Body Localization Using Mixture of Nonlinear Shape Models
  J. Zhang, R. Collins, and Y. Liu
  International Conference of Computer Vision (ICCV'05), October, 2005, pp. 725 - 732. [Abstract]
  Download: pdf [1702 KB] copyrighted

• SVM Decision Boundary Based Discriminative Subspace Induction
  J. Zhang and Y. Liu
  Pattern Recognition, Vol. 38, No. 10, October, 2005, pp. 1746 - 1758. [Abstract]
  Download: pdf [645 KB] copyrighted

• Cervical Cancer Detection Using SVM Based Feature Screening
  J. Zhang and Y. Liu
  Proceedings of the 7th International Conference on Medical Image Computing and Computer Aided Intervention (MICCAI '04), Vol. II, September, 2004, pp. 873 - 880.
  Download: pdf [850 KB] copyrighted

• Representation and Matching of Articulated Shapes
  J. Zhang, R. Collins, and Y. Liu
  Proceedings of the 2004 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'04), Vol. II, June, 2004, pp. 342 - 349. [Abstract]
  Download: pdf [1640 KB] copyrighted

• Does Multispectral Texture Features Really Improve Cervical Cancer Detection?
  T. Zhao, J. Zhang, and Y. Liu
  International Conference on Diagnostic Imaging and Analysis (ICDIA 2002), August, 2002.
  Download: pdf [127 KB] copyrighted

• SVM Based Feature Screening Applied to Hierarchical Cervial Cancer Detection
  J. Zhang, Y. Liu, and T. Zhao
  International Conference on Diagnostic Imaging and Analysis (ICDIA 2002), August, 2002. [Abstract]
  Download: pdf [488 KB] copyrighted

• Learning Multispectral Texture Features for Cervical Cancer Detection
  Y. Liu, T. Zhao, and J. Zhang
  Proceedings of 2002 IEEE International Symposium on BiomedicalImaging: Macro to Nano, July, 2002, pp. 169 - 172. [Abstract]
  Download: pdf [554 KB], ps.gz [876 KB] copyrighted

• SVM Decision Boundary Based Discriminative Subspace Induction
  J. Zhang and Y. Liu
  tech. report CMU-RI-TR-02-15, Robotics Institute, Carnegie Mellon University, June, 2002. [Abstract]
  Download: pdf [547 KB], ps.gz [326 KB] copyrighted