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Occlusion as a Monocular Depth Cue Derived from Illusory Contour Perception

机译:闭塞作为源自虚幻轮廓感知的单眼深度提示

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When a three dimensional scene is projected to the two dimensional receptive field of a camera or a biological vision system, all depth information is lost. Even without a knowledgebase, i.e. without knowing what object can be seen, it is possible to reconstruct the depth information. Beside stereoscopic depth cues, also a number of moncular depth cues can be used. One of the most important monocular depth cues ist the occlusion of object boundaries. Therefore one of the elaborated tasks for the low level image processing stage of a vision system is the completion of cluttered or occluded object boundaries and the depth assignment of overlapped boundaries. We describe a method for depth ordering and figure-ground segregation from monocular depth cues, namely the arrangement of so-called illusory contours at junctions in the edge map of an image. Therefore, a computational approach to the perception of illusory contours, based on the tensor voting technique, is introduced and compared with an alternative contour completion realized by spline interpolation. While most approaches assume, that the position of junctions and the orientations of associated contours are already known, we also consider the preprocessing steps that are necessary for a robust perception task. This implies the anisotropic diffusion of the input image in order to simplify the image contents while preserving the edge information.
机译:当三维场景被投射到相机或生物视觉系统的二维接收领域时,所有深度信息都会丢失。即使没有知识库,即,不知道可以看到对象,也可以重建深度信息。除立体深度提示外,还可以使用许多单曲深度线索。最重要的单曲深度提示之一是对象边界的闭塞。因此,视觉系统的低级图像处理阶段的阐述任务之一是完成杂乱或遮挡的物体边界和重叠边界的深度分配。我们描述了一种用于从单眼深度提示的深度排序和图形隔离的方法,即所谓的图像中的结处的所谓幻觉轮廓的布置。因此,引入了基于张量投票技术的虚幻轮廓感知的计算方法,并与用花键内插实现的替代轮廓完成相比。虽然大多数方法假设,所以结束的位置和相关轮廓的取向已经已知,我们还考虑了鲁棒的感知任务所需的预处理步骤。这意味着输入图像的各向异性扩散,以便在保留边缘信息的同时简化图像内容。

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