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Entropy-Based Localization of Textured Regions

机译:基于熵的纹理区域定位

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摘要

Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person's pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate. In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribution to measure if a texture is present in a region and applies a quad-tree method for texture segmentation. We performed experiments on a publicly available dataset and compared to a method at the state of the art [16]. Our experiments showed our method has satisfactory performance.
机译:外观描述是计算机视觉中的一个相关领域,它使领域中的对象识别成为重新标识,检索和分类。描述外观的重要线索是颜色和纹理。然而,在实际情况下,由于人的姿势改变时的遮挡和衣服的变形,质地检测是具有挑战性的。此外,在某些情况下,处理后的图像分辨率较低,并且现有技术中用于纹理分析的方法不合适。在本文中,我们处理了为服装描述目的而对真实纹理进行局部化的问题,例如条纹和/或复杂的图案。我们的方法使用原始分布的熵来衡量区域中是否存在纹理,并应用四叉树方法进行纹理分割。我们在公开可用的数据集上进行了实验,并与现有技术进行了比较[16]。我们的实验表明我们的方法具有令人满意的性能。

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