研究著作內容
DroneFace: An Open Dataset for Drone Research
(NOTE: Sheng-Wei Chen is also known as Kuan-Ta Chen.)

Abstract
In this paper, we present DroneFace, an open dataset for testing how well face recognition can work on drones. Because of the high mobility, drones, i.e. unmanned aerial vehicles (UAVs), are appropriate for surveillance, daily patrol or seeking lost people on the streets, and thus need the capability of tracking human targets' faces from the air. Under this context, drones' distances and heights from the targets influence the accuracy of face recognition. In order to test whether a face recognition technique is suitable for drones, we establish DroneFace composed of facial images taken from various combinations of distances and heights for evaluating how good a face recognition technique is in recognizing designated face from the air. Since Face recognition is one of the most successful application in image analysis and understanding, and there exist many face recognition database for various purposes. To the best of our knowledge, DroneFace is the only dataset including facial images take from controlled distances and heights within unconstrained environment, and can be valuable for future study of integrating face recognition techniques onto drones.

Materials
Citation
Hwai-Jung Hsu and Kuan-Ta Chen, "DroneFace: An Open Dataset for Drone Research," In Proceedings of ACM MMSys 2017 (Dataset Track), Jun 2017.

BibTex
@INPROCEEDINGS{hsu17:drone_face,
  AUTHOR     = {Hwai-Jung Hsu and Kuan-Ta Chen},
  TITLE      = {DroneFace: An Open Dataset for Drone Research},
  BOOKTITLE  = {Proceedings of ACM MMSys 2017 (Dataset Track)},
  MONTH      = {Jun},
  YEAR       = {2017}
}