基于形状特征的bovw图像分类方法,采用N-gram和空间金字塔编码方案

Elham Etemad, Gang Hu, Q. Gao
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引用次数: 3

摘要

图像分类是一项基于图像内容编码的通用视觉分析任务。在本研究中,我们提出了一种基于感知形状特征及其空间分布的图像表示方法。采用自然语言处理概念N-gram生成一组感知形状的视觉词,用于对图像特征进行编码。将分层视觉词与空间金字塔相结合,构建空间形状金字塔表示,减少语义缺口。实验结果表明,该方法优于其他先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A shape feature based bovw method for image classification using N-gram and spatial pyramid coding scheme
Image classification is a general visual analysis task based on the image content coded by its representation. In this research, we proposed an image representation method that is based on the perceptual shape features and their spatial distributions. A natural language processing concept, N-gram, is adopted to generate a set of perceptual shape visual words for encoding image features. By combining hierarchical visual words and spatial pyramid, Spatio-Shape Pyramid representation is constructed to reduce the semantic gaps. Experimental results show that the proposed method outperforms other state-of-the-art methods.
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