Design space exploration for adaptive privacy protection in airborne images
Airborne cameras on low-flying unmanned vehicles introduce new privacy challenges due to their mobility and viewing angles. In this paper, we focus on face recognition from airborne cameras and explore the design space to determine when a face in an airborne image is inherently protected, that is when an individual is not recognizable. Moreover, when individuals are recognizable by facial recognition algorithms, we propose an adaptive filtering mechanism to lower the face resolution in order to preserve privacy while ensuring a minimum reduction of the fidelity of the image. In particular, we estimate the resolution of faces captured at different altitudes and tilt angles using the data from navigation sensors and ascertain when the captured face is inherently protected. When the face is unprotected, we define a mechanism that automatically configures the strength of a privacy protection filter to improve the trade-off between privacy protection and fidelity of an aerial image or video.