Tracking with Integrated Features Matching and Adaptive Model Updating
Algorithms for correlation-based IR(infrared) target tracking can be implemented easily and having high precision, so they are used in many conditions. There are some problems to be solved for IR target tracking. The problems are how to realize steady and fast tracking and how to assure the validity of model updating. This paper proposes a novel high performance matching algorithm which includes integrated features selection and accelerate phase, then describes a model updating scheme based on confidence integration and multiple frame cumulation, the proposed IR target tracking algorithm can make the system be real time and matching results be accurate. From the experiment results we can conclude the proposed solution is validate and practical, and is very useful.
target tracking integrated features matching confidence model updating
Fei Huang Dehua Li
Institute for pattern Recognition and Artificial Intelligence at Huazhong University of Science and Institute for pattern Recognition and Artificial Intelligence at Huazhong University of Science and
国际会议
武汉
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）