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Global contour saliency and local colinear interactions.

机译:整体轮廓显着性和局部共线性相互作用。

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Our visual system can link components of contours and segregate contours from complex backgrounds based on geometric grouping rules. This is an important intermediate step in object recognition. The substrate for contour integration may be based on contextual interactions and intrinsic horizontal connections seen in primary visual cortex (V1). We examined the perceptual rules governing contour saliency to determine whether the spatial extents of contextual interactions and horizontal connections match those mediating saliency. To quantify these rules, we used stimuli composed of randomly oriented nonoverlapping line segments. Salient contours within this complex background were formed by colinear alignment of nearby segments. Contour detectability was measured using a 2-interval-forced-choice design. Contour detectability deteriorated with increasing spacing between contour elements and improved as the number of colinear line elements was increased. At short contour spacing, the detectability reached a plateau with alignment of a few line segments that together formed a contour subtending several visual degrees. At intermediate spacing, saliency built up progressively with a greater number of colinear lines, extending up to 30 degrees. When contour spacing was beyond a critical range (about 2 degrees ), however, the detectability dropped to chance levels, regardless of the number of colinear lines. Contour detectability was found to be a function not only of the relative spacing of contour elements with respect to the noise elements but also of the average density of the overall pattern. Furthermore, training significantly improved contour detection, increasing the critical spacing of line elements beyond which contours were no longer detectable. Our data suggest that global contour integration is based on mechanisms of limited spatial extent, comparable to the interactions observed in V1. These interactions can cascade over larger distances provided the spacing of stimulus elements is kept within a limited range.
机译:我们的视觉系统可以链接轮廓的组成部分,并根据几何分组规则将轮廓与复杂背景分开。这是对象识别中重要的中间步骤。用于轮廓整合的基质可以基于在主要视觉皮层(V1)中看到的上下文交互和固有的水平连接。我们检查了控制轮廓显着性的知觉规则,以确定上下文交互和水平连接的空间范围是否与中介显着性相匹配。为了量化这些规则,我们使用了由随机定向的不重叠线段组成的刺激。该复杂背景中的显着轮廓是通过附近线段的共线对齐形成的。使用2间隔强制选择设计测量轮廓检测能力。轮廓检测能力随着轮廓元素之间的间距的增加而恶化,并随着共线元素的数量增加而提高。在较短的轮廓间距下,可检测性达到了稳定,并对齐了几个线段,这些线段一起形成了一个对接几个视觉度的轮廓。在中间间隔处,显着性随着更多的共线线逐渐扩展,延伸到30度。但是,当轮廓间距超出临界范围(约2度)时,无论共线的数量如何,可检测性都会下降到偶然水平。发现轮廓可检测性不仅是轮廓元素相对于噪声元素的相对间隔的函数,而且还是整个图案的平均密度的函数。此外,训练显着改善了轮廓检测,增加了无法检测轮廓的线元素的临界间距。我们的数据表明,全局轮廓积分基于有限的空间范围的机制,与V1中观察到的交互作用相当。只要刺激元件的间距保持在有限范围内,这些相互作用就可以在更大的距离上级联。

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