SAIVT Thermal Feature Detection

SAIVT Thermal Feature Detection

Overview

The SAIVT-Thermal Feature Detection Database contains a number of images suitable for evaluating the performance of feature detection and matching in the thermal image domain.

The database includes conditions unique to the thermal domain such as non-uniformity noise; as well as condition common to other domains such as viewpoint changes, and compression and blur.

You can read our paper on eprints.

Contact Dr Simon Denman for further information.

Licensing

The SAIVT Thermal Feature Detection Database is © 2012 QUT and is licensed under the Creative Commons Attribution-ShareAlike 3.0 Australia License.

Attribution

To attribute this database, please include the following citation:

An exploration of feature detector performance in the thermal-infrared modality. Vidas, Stephen, Lakemond, Ruan, Denman, Simon, Fookes, Clinton B., Sridharan, Sridha, & Wark, Tim. (2011) In Bradley, Andrew, Jackway, Paul, Gal, Yaniv, & Salvado, Olivier (Eds.) Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications, IEEE , Sheraton Noosa Resort & Spa, Noosa, QLD, pp. 217-223. http://eprints.qut.edu.au/48161/

Acknowledging the database in your publications

In addition to citing our paper, we kindly request that the following text be included in an acknowledgements section at the end of your publications:

We would like to thank the SAIVT Research Labs at Queensland University of Technology (QUT) for freely supplying us with the SAIVT Thermal Feature Detection Database for our research.

Installing the database

Download and unzip the following archive:

SAIVT-ThermalFeatureDetection.tar.gz (187MB, md5sum: 73565fcc95ae987adf446dd2cbc6be4c)

A copy of the publication can be found at http://eprints.qut.edu.au/48161/, and is also included in this package (Vidas 2011 - An exploration of feature detector performance in the thermal-infrared modality.pdf).

Related publications of interest may be found on the following webpages:

Stephen Vidas articles on eprints
Other articles by Stephen Vidas.

The database has the following structure:

Each of the ten environments is allocated its own directory.
Within most of these directories, thermal-infrared and visible-spectrum data is separated into the thermal and visible subdirectories respectively
Within each of these subdirectories, a profile folder is present which contains a sequence of ideal (untransformed) images in 8-bit depth format.
The thermal subdirectories also contain a pure folder which contains identical images in their original 16-bit depth format (which is difficult to visualize).
Also within each thermal subdirectory there may be additional folders present.

Each of these folders contain images under a single, controlled image transformation, the acronyms for which are expanded at the end of this document. The level of transformation varies (generally increasing in severity) as the numerical label for each subfolder increases.

ACRONYMS:

CMP Image Compression
GAU Gaussian Noise
NRM Histogram Normalization
NUC Non-Uniformities Noise
OFB Out-of-focus Blur
QNT Quantization Noise
ROT Image Rotation
SAP Salt and Pepper Noise
TOD Time of day variation
VPT Viewpoint change

SAIVT 热图像特征检测数据库概述

本数据库汇集了一系列适用于评估热图像领域特征检测与匹配性能的图像。

数据库包含热图像领域特有的条件，如非均匀噪声；亦包含其他领域共有的条件，如视角变化、压缩和模糊等。

您可以阅读我们的论文，详情请见eprints。

如需进一步信息，请联系Simon Denman博士。

授权许可

SAIVT 热图像特征检测数据库由昆士兰科技大学（QUT）版权所有，2012年，并授权于Creative Commons Attribution-ShareAlike 3.0澳大利亚许可协议下。

致谢

为表明对本数据库的引用，请包含以下引用信息：

Vidas, Stephen, Lakemond, Ruan, Denman, Simon, Fookes, Clinton B., Sridharan, Sridha, & Wark, Tim. (2011) 在Bradley, Andrew, Jackway, Paul, Gal, Yaniv, & Salvado, Olivier (编辑)的《2011年国际数字图像计算：技术与应用会议论文集》，IEEE，Sheraton Noosa Resort & Spa，Noosa，QLD，第217-223页。http://eprints.qut.edu.au/48161/

在出版物中认可数据库

除了引用我们的论文外，我们还请求在您出版物的致谢部分包含以下文本：

我们感谢昆士兰科技大学（QUT）的SAIVT研究实验室为我们研究免费提供SAIVT热图像特征检测数据库。

数据库安装

下载并解压缩以下存档：

SAIVT-ThermalFeatureDetection.tar.gz (187MB, md5sum: 73565fcc95ae987adf446dd2cbc6be4c)

出版物的副本可在http://eprints.qut.edu.au/48161/找到，并包含在此包中（Vidas 2011 - An exploration of feature detector performance in the thermal-infrared modality.pdf）。

相关论文可在此网页上找到：

Stephen Vidas在eprints上的文章
Stephen Vidas的其他文章

数据库结构如下：

每个环境分配有其自己的目录。
在大多数这些目录中，热图像和可见光谱数据分别存储在热和可见子目录中。
在这些子目录中的每个子目录，都有一个包含一系列理想（未转换）图像的8位深度格式的配置文件文件夹。
热子目录还包含一个纯文件夹，其中包含原始16位深度格式的相同图像（难以可视化）。
在每个热子目录中，还可能有其他文件夹。

每个文件夹都包含在单一、受控的图像变换下的图像，其缩写词在文档末尾展开。随着每个子目录数值标签的增加，变换的程度（通常逐渐增加）。

缩写词：

CMP - 图像压缩
GAU - 高斯噪声
NRM - 直方图归一化
NUC - 非均匀性噪声
OFB - 失焦模糊
QNT - 量化噪声
ROT - 图像旋转
SAP - 盐和胡椒噪声
TOD - 白天时间变化