  In this work, we use a ceiling-mounted omni-directional camera to detect
people in a room. This can be used as a sensor to measure the occupancy of
meeting rooms and count the amount of flex-desk working spaces available. If
these devices can be integrated in an embedded low-power sensor, it would form
an ideal extension of automated room reservation systems in office
environments. The main challenge we target here is ensuring the privacy of the
people filmed. The approach we propose is going to extremely low image
resolutions, such that it is impossible to recognise people or read potentially
confidential documents. Therefore, we retrained a single-shot low-resolution
person detection network with automatically generated ground truth. In this
paper, we prove the functionality of this approach and explore how low we can
go in resolution, to determine the optimal trade-off between recognition
accuracy and privacy preservation. Because of the low resolution, the result is
a lightweight network that can potentially be deployed on embedded hardware.
Such embedded implementation enables the development of a decentralised smart
camera which only outputs the required meta-data (i.e. the number of persons in
the meeting room).
