Low complexity image matching using color based SIFT

Abhishek Nagar, A. Saxena, S. Bucak, Felix C. A. Fernandes, Kong-Posh Bhat
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引用次数: 2

Abstract

Image matching and search is gaining significant commercial importance nowadays due to various applications it enables such as augmented reality, image-queries for internet search, etc. Many researchers have effectively used color information in an image to improve its matching accuracy. These techniques, however, cannot be directly used for large scale mobile visual search applications that pose strict constraints on the size of the extracted features, computational resources and the system accuracy. To overcome this limitation, we propose a new and effective technique to incorporate color information that can use the SIFT extraction technique. We conduct our experiments on a large dataset containing around 33, 000 images that is currently being investigated in the MPEG-Compact Descriptors for Visual Search Standard and show substantial improvement compared to baseline.
基于彩色SIFT的低复杂度图像匹配
如今,图像匹配和搜索正在获得重要的商业重要性,因为它可以实现各种应用,如增强现实,互联网搜索的图像查询等。许多研究者已经有效地利用图像中的颜色信息来提高图像的匹配精度。然而,这些技术不能直接用于大规模的移动视觉搜索应用,这些应用对提取特征的大小、计算资源和系统精度都有严格的限制。为了克服这一限制,我们提出了一种新的有效的技术来融合颜色信息,可以使用SIFT提取技术。我们在一个包含大约33,000张图像的大型数据集上进行实验,这些图像目前正在MPEG-Compact Descriptors for Visual Search Standard中进行研究,与基线相比显示出实质性的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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