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Dataset Statistics


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.

Train-Test Split

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 )

  • To obtain the password for the compressed file, email the duly filled license agreement to with the subject line "License agreement for DroneSURF Database"
    NOTE: The license agreement has to be signed by someone having the legal authority to sign on behalf of the institute, such as the head of the institution or registrar. If a license agreement is signed by someone else, it will not be processed further.

    This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports, you must refer to the following paper:
  • I. Kalra, M. Singh, S. Nagpal, R. Singh, and M. Vatsa, DroneSURF: Benchmark Dataset for Drone-based Face Recognition, In IEEE International Conference on Automatic Face and Gesture Recognition, 2019.

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