Segmentation of transparent objects from sequences can be very useful in computer vision applications. However, without additional auxiliary information it can be hard work for traditional segmentation methods, as light in the transparent area captured by RGB cameras mostly derive from the background and the appearance of transparent objects changes with surroundings. In this article, we present a from‐coarse‐to‐fine transparent object segmentation method, which utilizes trajectory clustering to roughly distinguish the transparent from the background and refine the segmentation based on combination information of color and distortion. We further incorporate the transparency saliency with color and trajectory smoothness throughout the video to acquire a spatiotemporal segmentation based on graph‐cut. We conduct our method on various datasets. The results demonstrate that our method can successfully segment transparent objects from the background.

中文翻译：

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从随意捕获的视频中进行透明对象分割

从序列中分割透明对象在计算机视觉应用中非常有用。然而，如果没有额外的辅助信息，传统的分割方法可能会很困难，因为 RGB 相机捕获的透明区域中的光线大多来自背景，并且透明物体的外观会随着环境而变化。在本文中，我们提出了一种从粗到细的透明物体分割方法，该方法利用轨迹聚类粗略区分透明物体和背景，并根据颜色和失真的组合信息细化分割。我们进一步将透明度显着性与整个视频中的颜色和轨迹平滑度结合起来，以获得基于图切割的时空分割。我们在各种数据集上执行我们的方法。