Sensor-level privacy for thermal cameras

As cameras turn ubiquitous, balancing privacy and utility becomes crucial. To achieve both, we enforce privacy at the sensor level, as incident photons are converted into an electrical signal and then digitized into image measurements. We present sensor protocols and accompanying algorithms that degrade facial information for thermal sensors, where there is usually a clear distinction between humans and the scene. By manipulating the sensor processes of gain, digitization, exposure time, and bias voltage, we are able to provide privacy during the actual image formation process and the original face data is never directly captured or stored. We show privacy-preserving thermal imaging applications such as temperature segmentation, night vision, gesture recognition and HDR imaging.