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	Intended motion estimation using fuzzy Kalman filtering for UAV image stabilization with large drifting
	Xin, Tiantian ; Zhao, Hongying ; Liu, Sijie ; Wang, Lu
	2015
英文摘要	Videos from a small Unmanned Aerial Vehicle (UAV) are always unstable because of the wobble of the vehicle and the impact of surroundings, especially when the motion has a large drifting. Electronic image stabilization aims at removing the unwanted wobble and obtaining the stable video. Then estimation of intended motion, which represents the tendency of global motion, becomes the key to image stabilization. It is usually impossible for general methods of intended motion estimation to obtain stable intended motion remaining as much information of video images and getting a path as much close to the real flying path at the same time. This paper proposed a fuzzy Kalman filtering method to estimate the intended motion to solve these problems. Comparing with traditional methods, the fuzzy Kalman filtering method can achieve better effect to estimate the intended motion. ? 2015 SPIE-IS&T.; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1117/12.2083102
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/412449]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Xin, Tiantian,Zhao, Hongying,Liu, Sijie,et al. Intended motion estimation using fuzzy Kalman filtering for UAV image stabilization with large drifting. 2015-01-01.

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