【2h】

Pre-attentive segmentation and correspondence in stereo.

机译:注意力集中的分割和立体声对应。

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摘要

Traditional stereo grouping models have focused on the problem of stereo correspondence between monocular inputs. Recent physiological data revealed that the disparity selective V2 cells increase their responses when (random-dot stereograms) stimuli within their receptive fields are at or near the boundary of a depth surface. Such highlights to depth (non-luminance) edges are seemingly not computationally required for the correspondence problem. Computationally, these highlights make the boundaries of a depth surface more salient, serving pre-attentive segmentation (between depth planes) and attracting visual attention. In special cases, they enable the psychophysically observed perceptual pop-out of a target from a background of visually identical distractors at a different depth. To achieve the highlights, mutual inhibition between disparity selective cells that are tuned to the same or similar depths is required. However, such mutual inhibition would impede the computation for the correspondence problem, which requires mutual excitation between the same cells. In this work, I introduce a computational model that, I believe, is the first to address both stereo correspondence and pre-attentive stereo segmentation. The computational mechanisms in the model are based on intracortical interactions in V2. I will demonstrate that the model captures the following physiological and psychophysical phenomena: (i) depth-edge highlighting; (ii) disparity capture; (iii) pop-out; and (iv) transparency.
机译:传统的立体声分组模型集中于单眼输入之间的立体声对应问题。最新的生理数据显示,当视域选择性V2细胞在其接受区域内的(随机点立体图)刺激位于深度表面的边界处或附近时,其反应会增强。对于对应问题,似乎不需要深度计算深度(非亮度)边缘。通过计算,这些高光使深度表面的边界更加显眼,有助于进行预先注意的分割(在深度平面之间)并吸引视觉注意力。在特殊情况下,它们可以从不同深度的视觉上相同的干扰物的背景上,从心理上观察到目标的感知弹出。为了获得亮点,需要调节到相同或相似深度的视差选择性单元之间的相互抑制。但是,这种相互禁止将妨碍对应问题的计算,该问题需要相同单元之间的相互激励。在这项工作中,我介绍了一个计算模型,我相信这是第一个解决立体声对应和预注意立体声分割的模型。该模型中的计算机制基于V2中的皮质内交互作用。我将演示该模型捕获以下生理和心理生理现象:(i)深度边缘突出显示; (ii)视差捕获; (iii)弹出式视窗; (iv)透明度。

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