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钟志ZHONG, ZHI

Research Assistant

  PhD, Shanghai Jiao Tong University

Address: MAE Department, The Chinese University of Hong Kong, Sha Tin, Hong Kong
    Tel: (852)26098062
    Fax: (852)26036002
Email: zzhong@mae.cuhk.edu.hk

Research Assistant, The Chinese University of Hong Kong

BRIEF BIO

He received the M.S. degree in electronics engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2004, and PhD degree from Shanghai Jiao Tong University, Shanghai, China, in 2008. From 2005, he became a Research Assistant in The Chinese University of Hong Kong, till now. His current research interests include computer vision, intelligent surveillance system, and robotics.

SELECTED PUBLICATIONS

(For a complete list of papers, please see the laboratory homepage)

  1. Zhi Zhong, Ning Ding, Weizhong Ye, Xinyu Wu, and Yangsheng Xu, "Robust People Counting in Complicated Situations", International Journal of ARM, Vol.9, No.2, pp.14-19, June, 2008.

  2. Zhi Zhong, Ning Ding, Xinyu Wu, and Yangsheng Xu, "Crowd Surveillance using Markov Random Fields", Proceedings of the IEEE International Conference on Automation and Logistics, pp.1822-1828, Qingdao, China, September 1-3, 2008.

  3. Zhi Zhong, Weizhong Ye, and Yangsheng Xu, "Detecting Human Abnormal Behaviors in Crowd", International Journal of Information Acquisition, Vol.4, No.4, pp.281-290, 2007.

  4. Zhi Zhong, Yangsheng Xu, Weiren Shi, Weizhong Ye, and Ka Keung Lee, "Crowd Abnormality Surveillance", Chinese Journal of Scientific Instrument, Vol.28, No.4, pp.614-620, April, 2007.

  5. Zhi Zhong, Ming Yang, Shengshu Wang, Weizhong Ye, and Yangsheng Xu, "Energy Methods for Crowd Surveillance", Proceedings of the 2007 International Conference on Information Acquisition, pp.504-510, Jeju City, Korea, July 9-11, 2007.

  6. Zhi Zhong, Weizhong Ye, Ming Yang, and Yangsheng Xu, "Crowd Energy and Feature Analysis", Proceedings of the 2007 IEEE International Conference on Integration Technology, pp.144-150, Shenzhen, China, March 20-24, 2007.

  7. Yufeng Chen, Zhi Zhong, Ka Keung Lee, and Yangsheng Xu, "Multi-agent Based Surveillance", Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2810-2815, Beijing China, October 9-15, 2006.

  8. Weizhong Ye, Yangsheng Xu, and Zhi Zhong, "Robust People Counting in Crowded Environment", Proceedings of the 2007 IEEE International Conference on Robotics and Biomimetics, pp.1133-1137, Sanya, China, December 15-18, 2007.

  9. Ming Yang, Zhongke Yin, Zhi Zhong, Shengshu Wang, Pei Chen, and Yangsheng Xu, "A Contourlet-based Method for Handwritten Signature Verification", Proceedings of the IEEE International Conference on Automation and Logistics, pp.1561-1566, Jinan, China, August 18-21, 2007.

  10. Shengshu Wang, Gewen Kang, Zhi Zhong, Ming Yang, Pei Chen, and Yangsheng Xu, "Foreground Detection Based on Real-time Background Modeling and Robust Subtraction", Proceedings of the IEEE International Conference on Automation and Logistics, pp.331-335, Jinan, China, August 18-21, 2007.

  11. Xinyu Wu, Haitao Gong, Pei Chen, Zhong Zhi, and Yangsheng Xu, "Intelligent household surveillance robot", Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, pp.1734-1739, Bangkok, Thailand, February 21 - 26, 2009.

  12. Xinyu Wu, Haitao Gong, Pei Chen, Zhi Zhong, and Yangsheng Xu, "Surveillance Robot Utilizing Video and Audio Information", Journal of Intelligent and Robotic Systems, Vol.55, No.4-5, pp.403-421, January, 2009.

RESEARCH PROJECTS

Crowd ModelingCrowd Modeling

Surveillance of a crowd of pedestrians in public places like squares and subway stations is a challenging issue to public security. The crisis might lurk in the motion of crowd. To deal with the above-mentioned problem, we establish a modeling approach called “crowd modeling” and have built up a series of surveillance systems for testing.

Video SurveillanceVideo Surveillance

We present a low–cost surveillance system to model and analyze human actions based on leaning by demonstration. By teaching the system the difference between normal and abnormal human motions, the computational model built inside the trained machines can automatically identify whether the newly observed behaviors require security interference.