  The emerging ``Floor plan from human trails (PfH)" technique has great
potential for improving indoor robot navigation by predicting the
traversability of occluded floors. This study presents an innovative approach
that replaces first-person-view sensors with a third-person-view monocular
camera mounted on the observer robot. This approach can gather measurements
from multiple humans, expanding its range of applications. The key idea is to
use two types of trackers, SLAM and MOT, to monitor stationary objects and
moving humans and assess their interactions. This method achieves stable
predictions of traversability even in challenging visual scenarios, such as
occlusions, nonlinear perspectives, depth uncertainty, and intersections
involving multiple humans. Additionally, we extend map quality metrics to apply
to traversability maps, facilitating future research. We validate our proposed
method through fusion and comparison with established techniques.
