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Feature coding via vector difference for image classification

机译:通过向量差进行特征编码以进行图像分类

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摘要

An effective image representation is important to an image classification task. The most popular image representation framework utilizes a feature coding algorithm to encode the extracted low-level feature descriptors into a vector representation. In this paper, we analyze the recently developed feature coding methods in a general way. According to their common characteristics, we propose a new coding scheme to perform feature coding based on the vector difference in a high-dimensional space which is obtained by explicit feature maps. As we illustrate, our method has promising results with small codebook sizes and generalizes most existing coding methods in a unified form.
机译:有效的图像表示对于图像分类任务很重要。最流行的图像表示框架利用特征编码算法将提取的低级特征描述符编码为矢量表示。在本文中,我们以一般的方式分析了最近开发的特征编码方法。根据它们的共同特征,我们提出了一种新的编码方案,该方案基于显式特征图获得的高维空间中的矢量差来执行特征编码。正如我们所说明的,我们的方法在小码本大小的情况下具有可喜的结果,并且以统一的形式概括了大多数现有的编码方法。

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