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首页> 外文会议>Seventh Neural Computation and Psychology Workshop Sep 17-19, 2001 Brighton, England >NATURAL SCENE PERCEPTION: VISUAL ATTRACTORS AND IMAGES PROCESSING
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NATURAL SCENE PERCEPTION: VISUAL ATTRACTORS AND IMAGES PROCESSING

机译：自然场景感知：视觉吸引者和图像处理

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摘要

This paper aims at identifying the regions of interest in natural scenes. These regions have been defined by a behavioural measure of eye movement and by a model of saliency map constructed in a biologically plausible manner. The saliency map codes the local region of interest in terms of signal properties such as contrast, orientation, colour, curvature etc. In our approach, pictures are processed using a retinal model, simulating the parvocellular output of the retina. The result is then filtered by a bank of Gabor filters, in mutual interaction in order to lower noise, enhance contour, and sharpen filter selectivity. Subjects' eye positions were recorded as they explored static black and white images in order to categorize these images. All fixations during one scene were averaged in order to make a density map coding the time spent for subjects on each pixel. Statistics were computed on the regions around the fixation point to evaluate an index of predictability of our saliency map. The saliency map and the density map select similar areas. Furthermore, statistics based on eye-selected regions show greater values than for randomly-selected ones.
机译：本文旨在确定自然场景中感兴趣的区域。这些区域是通过眼动的行为测量和以生物学上合理的方式构造的显着图模型定义的。显着图根据信号属性（例如对比度，方向，颜色，曲率等）对感兴趣的局部区域进行编码。在我们的方法中，使用视网膜模型处理图片，模拟视网膜的小细胞输出。然后，通过一堆Gabor过滤器对结果进行相互交互过滤，以降低噪声，增强轮廓并提高过滤器的选择性。在他们探索静态黑白图像以对这些图像进行分类时，记录他们的眼睛位置。对一个场景中的所有注视进行平均，以制作密度图，对每个像素上的对象花费的时间进行编码。对注视点周围的区域进行统计，以评估我们的显着性图的可预测性指标。显着图和密度图选择相似的区域。此外，基于眼睛选择区域的统计数据显示的值要大于随机选择区域的统计值。

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