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Active human visual segmentation in polar space by using segmentation by weighted aggregation method

机译:加权聚合分割法在极地空间中进行主动人眼视觉分割

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This paper presents a new idea in image segmentation algorithm driven by human visual system segmentation techniques and has been widely studied in the visual attention. The human eyes fixate at important locations in the scene, and every fixation point lies inside a particular region of arbitrary shape and size. we propose a method to segment the object of interest by finding the optimal closed contour around the fixation point in the polar space, The human visual system has two types of attention: overt attention (eye movements) and covert attention (without eye movement). For evaluating the segmentation result, from both region-based and boundary-based perspectives, are integrated into an objective function .Our approach can be complemented in a variety of ways, An interesting avenue has to do with learning models of the world. For example, if we had a model of a “squirrel,” we could segment the “squirrel,” more correctly in the region.
机译:本文提出了一种基于人类视觉系统分割技术的图像分割算法的新思路,并在视觉注意方面进行了广泛的研究。人眼注视场景中的重要位置,每个注视点位于任意形状和大小的特定区域内。我们提出了一种通过在极空间中的固定点周围找到最佳的闭合轮廓来分割目标对象的方法。人的视觉系统有两种注意力类型:显性注意力(眼动)和隐性注意力(无眼动)。为了评估分割结果,将基于区域和基于边界的观点整合到目标函数中。我们的方法可以通过多种方式进行补充,其中有趣的途径与世界学习模型有关。例如,如果我们有一个“松鼠”模型,我们可以在该区域中更正确地分割“松鼠”。

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