Drone Surveillance of Faces, is a large-scale drone dataset intended to facilitate research for face recognition using drones.
Data has been captured at two outdoor locations: (i) at the ground level, where subjects are asked to walk in a park-like environment, and (ii) at the terrace of a building. For each location and surveillance scenario, data is captured twice: (i) during the morning and (ii) during the evening, before sunset.
For each combination of location, surveillance use case, and time of capture, there exist 25 videos featuring 58 subjects. Each subject belongs to the age bracket of (18, 40) years, and each video contains subjects appearing in groups of 2-3. For a particular setting combination, one group appears in only one video. Since there exist eight combinations of location, surveillance scenario, and time of capture, each group of subjects occur in eight videos, thus resulting in a total of 200 videos. The subjects and pairings remain consistent across different settings.
The directory structure represents the combination of location, use case and time of capture.
Active Surveillance
Passive Surveillance
Dataset Challenges
We provide the ground truth annotations for each subject in each video, the high-quality gallery images of each subject and the recommended train-test splits.
Baseline Results-
Detection Baseline
Recognition Baseline
The database can be downloaded from the following link.
DroneSURF Database (12.6 GB) (CRC-32: E1CE8891 , MD5: E9CEC01591E7ABB46FA880B52B1C8CF7 )