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In Search of Perceptually Salient Groupings

机译:寻找可感知的显着分组

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摘要

Finding meaningful groupings of image primitives has been a long-standing problem in computer vision. This paper studies how salient groupings can be produced using established theories in the field of visual perception alone. The major contribution is a novel definition of the Gestalt principle of Prägnanz, based upon Koffka''s definition that image descriptions should be both stable and simple. Our method is global in the sense that it operates over all primitives in an image at once. It works regardless of the type of image primitives and is generally independent of image properties such as intensity, color, and texture. A novel experiment is designed to quantitatively evaluate the groupings outputs by our method, which takes human disagreement into account and is generic to outputs of any grouper. We also demonstrate the value of our method in an image segmentation application and quantitatively show that segmentations deliver promising results when benchmarked using the Berkeley Segmentation Dataset (BSDS).
机译:在计算机视觉中,寻找有意义的图像基元分组一直是一个长期存在的问题。本文研究了如何仅使用视觉感知领域中的既有理论就可以产生显着分组。主要的贡献是根据科夫卡的定义(即图像描述应该既稳定又简单),对Prägnanz格式塔定律的新颖定义。我们的方法是全局的,因为它可以一次操作图像中的所有图元。它可以工作,而与图像基元的类型无关,并且通常与图像属性(例如强度,颜色和纹理)无关。设计了一种新颖的实验来通过我们的方法定量评估分组的输出,该方法考虑了人类的不同意见,并且对任何石斑鱼的输出都是通用的。我们还展示了我们的方法在图像分割应用中的价值,并定量显示了使用伯克利分割数据集(BSDS)进行基准测试时,分割可提供令人鼓舞的结果。

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