A Survey on Moving Target Tracking in the Intelligent Visual Monitoring System

Abstract:

Moving target tracking is the key part of intelligent visual surveillance system. Among the various tracking algorithms, the Beysian tracking algorithms and the kernel tracking algorithm are two algorithms that frequently used. The Beysian tracking algorithms mainly conclude Kalman filtering algorithm, extended Kalman filtering algorithm and particle filtering algorithm. Mean Shift is the most representative algorithm of the kernel target tracking. In this survey, the status and development of target tracking algorithms has been studied more extensively with providing a few examples of modified tracking algorithms. Then a comparison was presented based on the limitations and scope of applications. Finally, the paper showed further research prospects of moving target tracking are introduced.

• Periodical: Applied Mechanics and Materials (Volumes 599-601)
• Pages: 790-793
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.599-601.790
• Online since: August 2014
• Authors: Meng Xin Li*, Gao Ling Su, Jing Hou, Dai Zheng
• Keywords: Extend Kalman Filtering, Kalman Filtering, Mean Shift, Moving Target Tracking, Particle Filtering

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