MODIFICATIONS: changed the Create_a_dataset_from_vidoes_and_labels.m file to convert the given MATLAB dataset into yolov5 format. Follow the instructions in the file's comments.
Dataset containing IR, visible and audio data that can be used to train and evaluate drone detection sensors and systems.
Video labels: Airplane, Bird, Drone and Helicopter. Audio labels: Drone, Helicopter and Background.
The dataset contains 90 audio clips and 650 videos (365 IR and 285 visible). If all images are extracted from all the videos the dataset has a total of 203328 annotated images.
Free to download, use and edit. Descriptions of the videos are found in "Video_dataset_description.xlsx". The videos can be used as they are, or together with the respective label-files. The annotations are in .mat-format and have been done using the Matlab video labeler. Some instructions and examples are found in "Create_a_dataset_from_videos_and_labels.m"
Please cite:
"Svanström F. (2020). Drone Detection and Classification using Machine Learning and Sensor Fusion".
Link to thesis
or
"Svanström F, Englund C and Alonso-Fernandez F. (2020). Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors".
Link to ICPR2020-paper
or
"Svanström F, Alonso-Fernandez F and Englund C. (2021). A Dataset for Multi-Sensor Drone Detection".
Link to Data in Brief
Contact:
[email protected]