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Extracting salient lines by Visual Attention for omnidirectional image classification

机译:通过视觉注意力提取突出线,用于全向图像分类

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representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene, which probably are useful in image classification. The proposed method is inspired from the Visual Attention, which is a perceptual mechanism in human and other primates that direct their perceptions to the limited regions of the scene. The attended regions are usually valuable in performing the task. Since the approach of using the lines to classify the images is particularly useful for omnidirectional images, we specialize our method to deal with these kinds of images. In the experiments, we demonstrate how our proposed methods improve the image classification performance with processing only small parts of the input images.
机译:表示图像作为其密钥和有趣的线条的集合有助于图像理解和分类。 在本文中,我们提出了一种提取场景的重要和有趣线路的方法,这可能在图像分类中有用。 该方法的启发是从视觉关注的启发,这是人类和其他灵长类动物的感知机制,它将其对现场有限地区引起的。 出席的地区通常在执行任务方面是有价值的。 由于使用线路对图像进行分类的方法对于全向图像特别有用,我们专注于处理这些类型的图像的方法。 在实验中,我们展示了我们所提出的方法如何改善图像分类性能,仅通过处理输入图像的小部分来改善图像分类性能。

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