使用基于骨架的权重函数简化对象

A. Hajdu, C. Giamas, I. Pitas
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引用次数: 5

摘要

在本文中,我们提出了一种新的模板简化方法,该方法使用模板在图像中找到感兴趣的对象。通过这种方式,我们提高了计算性能,因为使用简化模板匹配的模板点更少。此外,我们通过关注模板的主要形状行为(骨架)来保持模板点,从而提高了匹配的可靠性。简化的理论背景是通过质心Voronoi镶嵌框架推导出来的。通过热图像中人体外观的检测,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object Simplification Using a Skeleton-Based Weight Function
In this paper, we present a novel method for template simplification, where the template is used to find interesting objects within an image. In this way, we improve computational performance since less template points are matched using a simplified template. Moreover, we increase the reliability of the matching as we keep template points with focusing on the main shape behavior (skeleton) of the template. The theoretical background of the simplification is derived through the centroidal Voronoi tessellation framework. The efficiency of the proposed approach is demonstrated with detecting human appearance in thermal images.
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