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Accurate Moving Cast Shadow Suppression Based on Local Color Constancy Detection

机译:基于局部颜色恒定检测的精确运动投影阴影抑制

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摘要

This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions.
机译:本文介绍了一种新颖的框架,用于检测和抑制真实视频序列中出现的大多数可能情况下的适当阴影区域。我们的方法不需要有关场景的先验知识,也不限于特定的场景结构。此外,即使在前景区域的颜色与阴影区域的颜色非常相似时出现伪装的情况下,该技术也可以检测到无色和彩色阴影。由于对阴影区域的反射抑制,该方法利用了局部颜色恒定性。为了检测场景中的阴影区域,将背景图像的值除以RGB颜色空间中当前帧的值。我们展示了如何使用此亮度比来识别具有低梯度恒定性的片段,从而将阴影与前景区分开。在一系列公开可用的数据集上的实验结果表明,与最复杂,最先进的阴影检测算法相比,我们的方法具有优越的性能。这些结果表明,我们的方法在各种阴影类型和具有挑战性的视频条件下都是可靠且准确的。

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