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	AMSAC: An adaptive robust estimator for model fitting
	Wang, Hanzi ; Cai, Jinlong ; Tang, Jianyu ; Wang HZ(王菡子)
	2013
关键词	Image processing
英文摘要	Conference Name:2013 20th IEEE International Conference on Image Processing, ICIP 2013. Conference Address: Melbourne, VIC, Australia. Time:September 15, 2013 - September 18, 2013.; The Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society; In this paper, we firstly propose a novel robust scale estimator called AIKOSE. It can estimate the scale of inlier noises by adaptively selecting the optimal value of K in the IKOSE scale estimator. Moreover, based on AIKOSE, we propose a novel robust estimator called AMSAC, which can fit a model without requiring a manually tuned threshold. In the experiments, we demonstrate the performance of AMSAC on line fitting and homography estimation by using both synthetic data and real images. Experimental results show that AM-SAC is more robust than other competing robust estimators. ? 2013 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/ICIP.2013.6738063
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86577]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Wang, Hanzi,Cai, Jinlong,Tang, Jianyu,et al. AMSAC: An adaptive robust estimator for model fitting. 2013-01-01.

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