Nienaber Potholes 1 Simplex

Dataset from the paper:

**"Detecting potholes with monocular computer vision: A performance evaluation of techniques" by Sonja Nienaber**

Supervisor: Dr. MJ Booysen

Department of Electrical & Electronic Engineering, Stellenbosch University

Co-supervisor: Dr. RS Kroon

Computer Science Division, Stellenbosch University

March 2016

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The entire dataset consists of two different sets, one was considered to be simple and the other more complex.
These datasets do share some files and there are a few instances where two different images would have the same name.
Therefore, the appropriate measures need to be taken if the data is combined into one larger dataset.

Each of the datasets contain folders containing the training (positive and negative) images as well as a set of positive test images.

Credit also goes to:

- S. Nienaber, M.J. Booysen, R.S. Kroon, “Detecting potholes using
simple image processing techniques and real-world footage”, SATC,
July 2015, Pretoria, South Africa.
- S. Nienaber, R.S. Kroon, M.J. Booysen , “A Comparison of Low-Cost
Monocular Vision Techniques for Pothole Distance Estimation”, IEEE
CIVTS, December 2015, Cape Town, South Africa.

本数据集源自论文《利用单目计算机视觉检测路面坑洼：技术性能评估》由Sonja Nienaber所著。指导教师为MJ Booysen博士，所属院系为 Stellenbosch 大学电气与电子工程学院。联合指导教师为RS Kroon博士，所属院系为 Stellenbosch 大学计算机科学系。研究时间为2016年3月。数据集由两个不同集合组成，其中之一被认定为简单，而另一个则较为复杂。这两个数据集共享部分文件，且存在某些情况下，两幅不同的图像具有相同的名称。因此，若将数据合并为一个更大的数据集，需采取适当的措施。每个数据集包含包含训练（正负样本）图像以及一组正样本测试图像的文件夹。此外，以下文献亦应受到认可：S. Nienaber, M.J. Booysen, R.S. Kroon，“利用简单的图像处理技术和现实世界视频检测路面坑洼”，SATC，2015年7月，南非比勒陀利亚；S. Nienaber, R.S. Kroon, M.J. Booysen，“低成本单目视觉技术在路面坑洼距离估计中的应用比较”，IEEE CIVTS，2015年12月，南非开普敦。”}