Counting moving people by staring at a blank wall

Abstract

We present a passive non-line-of-sight imaging method that seeks to count hidden moving people from the observation of a uniform receiver such as a blank wall. The technique amplifies imperceptible changes in indirect illumination in videos to reveal a signal that is strongly correlated with the activity taking place in the hidden part of a scene. We use this signal to predict from a video of a blank wall whether moving persons are present, and to estimate their number. To this end, we train a neural network using data collected under a variety of viewing scenarios. We find good overall accuracy in predicting whether the room is occupied by zero, one or two persons, and analyze the generalization and robustness of our method with both real and synthetic data.