Abstract
This paper presents techniques for tracking non-line-ofsight (NLOS) objects using speckle imaging. We develop
a novel speckle formation and motion model where both
the sensor and the source view objects only indirectly via
a diffuse wall. We show that this NLOS imaging scenario is
analogous to direct LOS imaging with the wall acting as a
virtual, bare (lens-less) sensor. This enables tracking of a
single, rigidly moving NLOS object using existing specklebased motion estimation techniques. However, when imaging multiple NLOS objects, the speckle components due to
different objects are superimposed on the virtual bare sensor image, and cannot be analyzed separately for recovering the motion of individual objects. We develop a novel
clustering algorithm based on the statistical and geometrical properties of speckle images, which enables identifying
the motion trajectories of multiple, independently moving
NLOS objects. We demonstrate, for the first time, tracking
individual trajectories of multiple objects around a corner
with extreme precision (< 10 microns) using only off-theshelf imaging components