Turning Corners into Cameras: Principles and Methods

Abstract

We show that walls, and other obstructions with edges, can be exploited as naturally-occurring "cameras" that reveal the hidden scenes beyond them. In particular, we demonstrate methods for using the subtle spatio-temporal radiance variations that arise on the ground at the base of a wall's edge to construct a one-dimensional video of the hidden scene behind the wall. The resulting technique can be used for a variety of applications in diverse physical settings. From standard RGB video recordings, we use edge cameras to recover 1-D videos that reveal the number and trajectories of people moving in an occluded scene. We further show that adjacent wall edges, such as those that arise in the case of an open doorway, yield a stereo camera from which the 2-D location of hidden, moving objects can be recovered. We demonstrate our technique in a number of indoor and outdoor environments involving varied floor surfaces and illumination conditions.

Passive optical time-of-flight for non line-of-sight localization

“…In recent years, there have been great advancements in the development of techniques that enable non-line of sight (NLOS) optical imaging for a variety of applications, ranging from microscopic imaging through scattering tissue to around-the-corner imaging [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17]. The enabling principle behind these techniques is the use of scattered light for computational reconstruction of objects that are hidden from direct view.…”

“…The enabling principle behind these techniques is the use of scattered light for computational reconstruction of objects that are hidden from direct view. This has been achieved in a variety of approaches, such as wavefront shaping [12], inverseproblem solutions based on intensity only imaging [17,18], speckle correlations [13,14], and time-resolved measurements [3,4,5,6,7,9,10]. While wavefront-shaping approaches allow diffraction-limited resolution, they require prior access to the target position or long iterative optimization procedures.…”

Direct Object Recognition Without Line-Of-Sight Using Optical Coherence

“…Object recognition is essential for various applications such as face recognition, industrial inspection, medical imaging, and autonomous driving. One intriguing area of research is the recognition of objects without direct line-ofsight [1,3,4,13,17,19,20,27,28,39]. The ability to carry out recognition without line-of-sight has practical significance; for example, in autonomous driving, if the imaging system can recognize pedestrians and vehicles that are "hidden" around the corner or behind other obstacles, the vehicle can prevent potential hazards and greatly increase the safety level of driving.…”

Computational periscopy with an ordinary digital camera

“…The NLOS resolution is based on computational inversion of the influence of the scene of interest on the penumbra of an occluding object of known size and shape that is in an a priori unknown position. Previous exploitations of penumbrae required precise knowledge of occluder positions and used laser illumination and SPAD-based detection 25,26 , required occluder motion 27 , or had the more limited objective of producing a one-dimensional projection of the moving portion of a scene 28 . A very recent work uses calibration measurements of a complex occluder in a light field reconstruction 29 .…”