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Guided lazy snapping for long thin object selection

机译:引导式延迟捕捉,可长期选择薄对象

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We show a novel way to select long thin objects in an image by enhancing the output of the existing foreground/background image segmentation methods. Most superpixel-based methods fail to select the long thin details, such as legs and whiskers, and extended curves from the main objects. We observe, however, the output without long thin details, can be used as the guided information to obtain the connected components. Based on this observation, our Guided Lazy Snapping method overcomes the limitation of the Lazy Snapping methods (or other alternatives superpixel-based segmentation method) to select long thin objects. The results show that connected components in the image can be selected without having a lot of user interactions (mouse clicks) on each extended parts of the object.
机译:我们展示了一种通过增强现有前景/背景图像分割方法的输出来选择图像中长而细的对象的新颖方法。大多数基于超像素的方法无法选择长而细的细节,例如腿和胡须以及从主要对象延伸的曲线。但是,我们观察到,没有长而细的细节的输出可以用作获取连接组件的指导信息。基于此观察结果,我们的“引导式懒惰捕捉”方法克服了“懒​​惰捕捉”方法(或其他基于超像素的分割方法)在选择长而薄的对象方面的局限性。结果表明,可以选择图像中的已连接组件,而无需在对象的每个扩展部分上进行很多用户交互(鼠标单击)。

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