Interest point detection is one of the most fundamental and critical problems in computer vision and image processing. In this paper, we carry out a comprehensive review on image feature information (IFI) extraction techniques for interest point detection. To systematically introduce how the existing interest point detection methods extract IFI from an input image, we propose a taxonomy of the IFI extraction techniques for interest point detection. According to this taxonomy, we discuss different types of IFI extraction techniques for interest point detection. Furthermore, we identify the main unresolved issues related to the existing IFI extraction techniques for interest point detection and any interest point detection methods that have not been discussed before. The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed. Moreover, future research directions on IFI extraction techniques for interest point detection are elaborated.
翻译：利益点探测是计算机视觉和图像处理中最根本和最关键的问题之一。在本文件中,我们全面审查了图像特征信息提取技术,以便检测利益点。为了系统地介绍现有利益点检测方法如何从输入图像中提取国际融资机构,我们建议对国际金融机构提取技术进行分类,以便检测利益点。根据这一分类,我们讨论国际金融机构为检测利益点而采用的不同类型提取技术。此外,我们确定了与现有国际融资机构为检测利益点而采用的提取技术有关的主要未决问题,以及以前未曾讨论过的任何利益点检测方法。提供了现有的流行数据集和评估标准,并对18种最新方法的绩效进行了评估和讨论。此外,还详细制定了国际金融机构为检测利益点而采用提取技术的未来研究方向。
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