IEEE Trans Cybern. 2015 Aug;45(8):1575-86. doi: 10.1109/TCYB.2014.2356200. Epub 2014 Oct 1.
The human visual system (HVS) can reliably perceive salient objects in an image, but, it remains a challenge to computationally model the process of detecting salient objects without prior knowledge of the image contents. This paper proposes a visual-attention-aware model to mimic the HVS for salient-object detection. The informative and directional patches can be seen as visual stimuli, and used as neuronal cues for humans to interpret and detect salient objects. In order to simulate this process, two typical patches are extracted individually and in parallel from the intensity channel and the discriminant color channel, respectively, as the primitives. In our algorithm, an improved wavelet-based salient-patch detector is used to extract the visually informative patches. In addition, as humans are sensitive to orientation features, and as directional patches are reliable cues, we also propose a method for extracting directional patches. These two different types of patches are then combined to form the most important patches, which are called preferential patches and are considered as the visual stimuli applied to the HVS for salient-object detection. Compared with the state-of-the-art methods for salient-object detection, experimental results using publicly available datasets show that our produced algorithm is reliable and effective.
人类视觉系统 (HVS) 能够可靠地感知图像中的显著物体，但在没有图像内容先验知识的情况下，计算模型检测显著物体仍然具有挑战性。本文提出了一种视觉注意感知模型，以模拟 HVS 进行显著物体检测。信息丰富和方向的补丁可以被视为视觉刺激，并用作人类解释和检测显著物体的神经元线索。为了模拟这个过程，分别从强度通道和判别颜色通道中提取两个典型的补丁作为基元，分别进行独立和并行的提取。在我们的算法中，使用改进的基于小波的显著补丁检测器来提取视觉信息丰富的补丁。此外，由于人类对方向特征敏感，并且方向补丁是可靠的线索，我们还提出了一种提取方向补丁的方法。这两种不同类型的补丁然后组合形成最重要的补丁，称为优先补丁，并被认为是应用于 HVS 进行显著物体检测的视觉刺激。与用于显著物体检测的最新方法相比，使用公开可用数据集进行的实验结果表明，我们的算法是可靠和有效的。
