  Non-Line-of-Sight (NLOS) imaging aims at recovering the 3D geometry of
objects that are hidden from the direct line of sight. In the past, this method
has suffered from the weak available multibounce signal limiting scene size,
capture speed, and reconstruction quality. While algorithms capable of
reconstructing scenes at several frames per second have been demonstrated,
real-time NLOS video has only been demonstrated for retro-reflective objects
where the NLOS signal strength is enhanced by 4 orders of magnitude or more.
Furthermore, it has also been noted that the signal-to-noise ratio of
reconstructions in NLOS methods drops quickly with distance and past
reconstructions, therefore, have been limited to small scenes with depths of
few meters. Actual models of noise and resolution in the scene have been
simplistic, ignoring many of the complexities of the problem. We show that SPAD
(Single-Photon Avalanche Diode) array detectors with a total of just 28 pixels
combined with a specifically extended Phasor Field reconstruction algorithm can
reconstruct live real-time videos of non-retro-reflective NLOS scenes. We
provide an analysis of the Signal-to-Noise-Ratio (SNR) of our reconstructions
and show that for our method it is possible to reconstruct the scene such that
SNR, motion blur, angular resolution, and depth resolution are all independent
of scene size suggesting that reconstruction of very large scenes may be
possible. In the future, the light efficiency for NLOS imaging systems can be
improved further by adding more pixels to the sensor array.
