Fuzzy knowledge based enhanced matting

Charles Z. Liu, M. Kavakli
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引用次数: 4

Abstract

The goal of this paper is to address how to use human experience to develop an enhanced matting strategy. Based on a recursive α optimization framework, we present an adaptive fuzzy learning strategy for enhancement of matting. Taking into account the uncertainty of data, the proposed scheme successfully applies the expert human knowledge into matting. Experimental results are given to demonstrate the effect of the proposed method compared to some classical methods. The results indicate that the proposed adaptive learning algorithm handles uncertain pixels and perform stable matting.
基于模糊知识的增强抠图
本文的目标是解决如何利用人类经验来制定增强的消光策略。基于递归α优化框架,提出了一种自适应模糊学习策略来增强抠图。该方案考虑了数据的不确定性,成功地将人类的专业知识应用到消光中。实验结果表明,与一些经典方法相比,该方法是有效的。结果表明,所提出的自适应学习算法能够处理不确定像素,并能稳定地进行抠图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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