An Open Dataset for Testing Face Recognition on Drones
To use this data container in another docker execution perform the following steps:
1. Create a new container with:
2. Attach it as a volume to another container with:
The Drone Face data will be available under
/data in the new container.
DroneFace contains following contents:
11 subjects including 7 males and 4 females.
2,057 pictures including 620 raw images, 1,364 frontal face images, and 73 portrait images
The raw images are taken in 3,680x2,760 resolution with ultra-wide field of view (170◦) under daylights.
The resolutions of the facial images are between 23x31 and 384x384.
The raw images are taken from 1.5, 3, 4, and 5 meters high.
- The raw images are taken 2 to 17 meters away from the subjects with 0.5 meters interval.
- The 3-direction portrait images are taken by sport and phone camera for comparison.
All the images in DroneFace are named in the following manner:
11 subjects are named with English letters, a to k. The subject a, b, c, e, g, j, and k are males, and the remainders are females. If the subjectID part contains merely one letter means only one subject is in the image; on the other hand, there are multiple ones. The code “gp” in cameraType means the picture is taken using our sport camera (GoPro Hero3+ Silver Edition), and “cam” indicates that the pictures is taken using the HTC One M8 smart phone. heightID 0, 3, 4, and 5 represents that the camera is 1.5, 3, 4, and 5 meters high from the ground accordingly while the picture is taken. imageType “eo” means that the picture is a raw image, “ef” means thay the image is a frontal facial image extracted from a raw image, “por” means that the picture is the portrait handed by the subject, and “porF”, “porL”, or “porR” means the pictures is the portrait images of the subjects’ front, left, or right faces. The distance ID is a two digit number, and the actual distance from the subject to the camera equals to 17-(distanceID/2) meters. For any of the components in the filename, “na” represents that the corresponding information is not available.
 Hwai-Jung Hsu and Kuan-Ta Chen. 2015. Face Recognition on Drones: Issues and Limitations. In Proceedings of the First Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use (DroNet ‘15). ACM, New York, NY, USA, 39-44. DOI=http://dx.doi.org/10.1145/2750675.2750679
 Hwai-Jung Hsu and Kuan-Ta Chen. 2017. DroneFace: An Open Dataset for Drone Research. In Proceedings of the 8th ACM on Multimedia Systems Conference (MMSys’17). ACM, New York, NY, USA, 187-192. DOI: https://doi.org/10.1145/3083187.3083214
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