Abstract
The tracking of video moving target is actually an estimation problem of state variable. Kalman filter method is one of the classical estimators widely used in the field of state estimation. But in tracking system of video moving target, the classical Kalman filtering method has the problem of low tracking accuracy and divergence of filtering. In order to improve the tracking effect, a unscented Kalman filter algorithm is used to track moving target in video sequence. The application of unscented Kalman filter in tracking of video moving target is compared with that of Kalman filter by Matlab simulation software. The results show that unscented Kalman filter is more accurate and better than Kalman filter in tracking of video moving target.
Fund Project: National College Student Innovation Training Project Funding (No. 201810531017, 201108531019); Jishou University School-level University Student Innovation Project Funding (No. JDCX2018040); Jishou University 13th Five-Year Communication Engineering Specialty Comprehensive Reform Pilot Construction Project; Hunan Province first-class undergraduate communication engineering professional construction project.
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Guo, Q., Zeng, C., Jiang, Z., Hu, X., Deng, X. (2019). Application of Unscented Kalman Filter in Tracking of Video Moving Target. In: Sun, Z., He, R., Feng, J., Shan, S., Guo, Z. (eds) Biometric Recognition. CCBR 2019. Lecture Notes in Computer Science(), vol 11818. Springer, Cham. https://doi.org/10.1007/978-3-030-31456-9_53
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DOI: https://doi.org/10.1007/978-3-030-31456-9_53
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