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Joint upsampling of random color distance maps for fast salient region detection

机译:联合随机采样颜色距离图以进行显着区域快速检测

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摘要

The human visual system is capable of rapid response, even in the presence of massive quantities of visual information. This is possible because it restricts the operation of further processing stages to a small, potentially important, subset of the incoming information. This mechanism is calledvisual attentionand is drawn by distinctive,visually salient, regions of the scene. Detection of visually salient regions is widely employed in vision-based applications, since a reduction in visual search space can lead to significant improvement in computational performance. Despite recent advances in salient region detection, most efforts have focused on improving accuracy, at the expense of increased execution time, significantly hindering their applicability. To address this, a fast and accurate salient region detection method is presented in this work, based on an efficient saliency estimate calledrandom color distance map. This estimate is joint upsampled into an accurate saliency map, which is assessed and compared to saliency maps obtained by other four state-of-the-art methods on the MSRA1K, MSRA10K and SED2 datasets, showing that it is highly competitive in both accuracy and execution time.
机译:即使存在大量的视觉信息,人类视觉系统也能够快速响应。这是可能的,因为它将后续处理阶段的操作限制为传入信息的一小部分(可能是重要的)子集。这种机制称为视觉注意,由场景的独特,视觉上显着的区域吸引。视觉显着区域的检测已广泛用于基于视觉的应用程序中,因为视觉搜索空间的减少可导致计算性能的显着提高。尽管最近在显着区域检测方面取得了进步,但大多数工作都集中在提高准确性上,但以增加执行时间为代价,这严重阻碍了其适用性。为了解决这个问题,在这项工作中提出了一种快速有效的显着区域检测方法,该方法基于有效的显着性估计值(称为随机色距离图)。将该估计值联合上采样到一个准确的显着图中,对它进行评估并与通过其他四个最新方法在MSRA1K,MSRA10K和SED2数据集上获得的显着图进行比较,表明该方法在准确性和准确性方面都极具竞争力。执行时间处理时间。

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