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Just-in-time outdoor color discrimination using adaptive similarity-based classifier

机译:使用基于自适应相似度的分类器实时进行室外颜色识别

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References(9) The color recognition and identification in operation time is a critical task in color-based computer vision applications. The main problem for recognizing the real color arises when the color characteristics are changed dynamically in the life time of a system. The outdoor color models which have been addressed by some researchers have serious practical limitations to employ in real applications. Moreover, due to high fluctuations in environment illumination, using conventional classifier for discriminating colors is a complicated task. In this paper, a just-in-time and model-free solution in order to discriminate outdoor colors on data driven modality is proposed. For this purpose, adaptive similarity-based classifier is utilized to track the color's data evolution during a day.
机译:参考文献(9)在基于颜色的计算机视觉应用中,操作时的颜色识别和识别是一项关键任务。当颜色特性在系统的生命周期中动态变化时,就会出现识别真实颜色的主要问题。一些研究人员提出的户外色彩模型在实际应用中存在严重的实际限制。此外,由于环境照明的高度波动,使用常规的分类器来区分颜色是一项复杂的任务。在本文中,提出了一种实时且无模型的解决方案,以区分基于数据驱动模式的室外颜色。为此,基于自适应相似度的分类器可用于跟踪一天中颜色的数据演变。

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