An Efficient Hola Filter for Saliency Detection

Donyarut Kakanopas, K. Woraratpanya
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引用次数: 3

Abstract

Currently, saliency detection plays an important role in a wide range of applications, such as image segmentation, image recognition, image retrieval, target detection, and so on. These applications require not only the precise saliency localization but also the precise saliency shape. However, most existing approaches did not focus on the precise saliency shape. Therefore, this paper proposes an efficient approach for obtaining the more precise saliency shape. The key contribution of this work is designing a set of Hola filters for more precise localization and sharp edge of detected saliency. Based on a challenging dataset divided into seven categories with different characteristics, experimental results showed that our proposed method outperformed the baselines in almost categories in terms of AUC performance.
一种用于显著性检测的高效Hola滤波器
目前,显著性检测在图像分割、图像识别、图像检索、目标检测等广泛的应用中发挥着重要作用。这些应用不仅需要精确的凸点定位,而且需要精确的凸点形状。然而,大多数现有的方法并没有关注精确的显著形状。因此,本文提出了一种获得更精确的显著形状的有效方法。这项工作的关键贡献是设计了一套Hola滤波器,用于更精确的定位和检测显著性的锐利边缘。基于一个具有挑战性的数据集,该数据集被分为7个具有不同特征的类别,实验结果表明,我们提出的方法在AUC性能方面几乎优于基线。
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