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How important is location information in saliency detection of natural images

机译:位置信息在自然图像显着性检测中的重要性

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摘要

Location information, i.e., the position of content in image plane, is considered as an important supplement in saliency detection. The effect of location information is usually evaluated by integrating it with the selected saliency detection methods and measuring the improvement, which is highly influenced by the selection of saliency methods. In this paper, we provide direct and quantitative analysis of the importance of location information for saliency detection in natural images. We firstly analyze the relationship between content location and saliency distribution on four public image datasets, and validate the distribution by simply treating location based Gaussian distribution as saliency map. To further validate the effectiveness of location information, we propose a location based saliency detection approach, which completely initializes saliency maps with location information and propagate saliency among patches based on color similarity, and discuss the robustness of location information's effect. The experimental results show that location information plays a positive role in saliency detection, and the proposed method can outperform most state-of-the-art saliency detection methods and handle natural images with different object positions and multiple salient objects.
机译:位置信息,即内容在图像平面中的位置,被视为显着性检测的重要补充。位置信息的效果通常是通过将其与所选的显着性检测方法集成在一起并评估改进来评估的,而显着性受选择显着性方法的影响很大。在本文中,我们提供了位置信息对于自然图像中显着性检测的重要性的直接和定量分析。我们首先分析了四个公共图像数据集上内容位置与显着性分布之间的关系,然后通过简单地将基于位置的高斯分布视为显着图来验证分布。为了进一步验证位置信息的有效性,我们提出了一种基于位置的显着性检测方法,该方法可以使用位置信息完全初始化显着性图,并根据颜色相似性在补丁之间传播显着性,并讨论位置信息效果的鲁棒性。实验结果表明,位置信息在显着性检测中起着积极的作用,并且该方法可以胜过大多数最新的显着性检测方法,并且可以处理具有不同对象位置和多个显着对象的自然图像。

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