在 omnidirectional 视觉上评估特征点 -- 2014 年实验报告
Feature points evaluation on omnidirectional vision with a photorealistic fisheye sequence -- A report on experiments done in 2014
AI总结：
本报告旨在2014年通过实验确定最适合鱼眼图像的特征检测器和描述符，以提高鱼眼视觉里程计和立体视觉在城市场景中的性能。
摘要：
这份报告：这是一份科学报告，提供了详细的参考文献、我们称之为 PFSeq 的数据集（'Photorealistic Fisheye Sequence'）并可在 https://doi.org/10.57745/DYIVVU 上获取，以及全面的实验。这项工作应被视为草案，是在我的博士论文《从鱼眼视频数据构建 3D 模型——应用于城市区域的定位》（2014 年）期间完成的 [Mor16]。这些结果从未发表过。目的是在自校准的背景下，找到最适合鱼眼图像的特征检测器和描述符，相机安装在汽车顶部并指向天顶（从而进行鱼眼视觉里程计和城市场景的立体视觉）。我们面临鸡与蛋的问题，因为我们无法利用准确的投影模型来实现最优的特征检测和描述，而我们恰恰需要良好的特征来进行校准（即计算相机的准确投影模型）。这份报告不包含新的特征算法。它不将标准特征算法与专为 omnidirectional 图像设计的算法进行比较（不幸的是）。它尚未经过同行评审。讨论已被翻译并增强，但实验尚未再次运行，报告也未根据状态-of-the-art 的发展进行更新（请将其视为 2014 年的报告）
英文摘要：
What is this report: This is a scientific report, contributing with a detailed bibliography, a dataset which we will call now PFSeq for ''Photorealistic Fisheye Sequence'' and make available at https://doi.org/10. 57745/DYIVVU, and comprehensive experiments. This work should be considered as a draft, and has been done during my PhD thesis ''Construction of 3D models from fisheye video data-Application to the localisation in urban area'' in 2014 [Mor16]. These results have never been published. The aim was to find the best features detector and descriptor for fisheye images, in the context of selfcalibration, with cameras mounted on the top of a car and aiming at the zenith (to proceed then fisheye visual odometry and stereovision in urban scenes). We face a chicken and egg problem, because we can not take advantage of an accurate projection model for an optimal features detection and description, and we rightly need good features to perform the calibration (i.e. to compute the accurate projection model of the camera). What is not this report: It does not contribute with new features algorithm. It does not compare standard features algorithms to algorithms designed for omnidirectional images (unfortunately). It has not been peer-reviewed. Discussions have been translated and enhanced but the experiments have not been run again and the report has not been updated accordingly to the evolution of the state-of-the-art (read this as a 2014 report).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
