Haocheng Le

Work place: Institue of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology Zhejiang Provincial United Key Laboratory of Embedded System Hangzhou, Zhejiang, 310023, China

E-mail: lhc7895123@sina.com


Research Interests: Computer systems and computational processes, Artificial Intelligence, Computer Vision, Pattern Recognition


Haocheng. Le received his B. Sc. degree in automation from Zhejiang University of Technology, China, in 2010, and he is currently a graduate student in Zhejiang University of Technology, China. His research interests include computer vision and pattern recognition, artificial intelligence, etc. 

Author Articles
Momentum Based Level Set Method For Accurate Object Tracking

By Haocheng Le Linglong Hu Yuanjing Feng

DOI: https://doi.org/10.5815/ijisa.2010.02.02, Pub. Date: 8 Dec. 2010

This paper proposes a novel object tracking method that is robust to a cluttered background and large motion. First, a posterior probability measure (PPM) is adopted to locate the object region. Then the momentum based level set is used to evolve the object contour in order to improve the tracking precision. To achieve rough object localization, the initial target position is predicted and evaluated by the Kalman filter and the PPM, respectively. In the contour evolution stage, the active contour is evolved on the basis of an object feature image. This method can acquire more accurate target template as well as target center. The comparison between our method and the kernelbased method demonstrates that our method can effectively cope with the deformation of object contour and the influence of the complex background when similar colors exist nearby. Experimental results show that our method has higher tracking precision.

[...] Read more.
Other Articles