MSDI: a geo-tagged drone imagery for absolute visual localization

The MSDI (Manchester Surface Drone Imagery) is a geo-imagery registration dataset. 
The dataset consists of 
a. 446 downward-facing drone images.
b. 89 forward-facing(45-degree) drone images.
c. 64 forward-facing (0-degree) drone images. 
d. parameter matrix of drone camera and transformation matrix.
e. checkerboard images for camera calibration.

This dataset is collected by Mochuan Zhan for his MSC project: Registration of UAV Imagery to Aerial and Satellite Imagery
in the University of Manchester (2021/9 - 2022/9) which is supervised by Dr.Terence Patrick Morley. This project aims at 
developing a system that could perform efficient UAV visual localization through image registration based on local feature 
detectors and the technique of high-throughput computing.

Notice:
The corresponding satellite image from Google Map and Bing Map could be obtained by my program, Link: 

https://doi.org/10.5281/zenodo.6977652

A Ground Control Point (GCP) selector is provided for user to select GCP and create file with small effort.
By registrating corresponding images, users could evaluate the performance of their registration techniques.

The Imagery contains images of 8 Areas in Manchester:
- Manchester Aquatics Center 80
- Manchester ASDA 76
- Manchester Bussiness School 37
- Manchester Energy Center 71
- Manchester Holy Name Church 58
- Manchester Hulme Park 47
- Manchester Hulme Part(0-degree) 64
- Manchester Hulme Part(45-degree) 89
- Manchester Metropolitan university 29 
- Manchester Museum 48

Device Information:
- Drone brand: Parrot
- Drone model: Parrot Anafi

Software Information:
- Pix4DCapture
- FreeFlight6

Flight parameters:
- Height 100m
- Speed 5m/s
- overlap low