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The emerging ``Floor plan from human trails (PfH)" technique has greatpotential for improving indoor robot navigation by predicting thetraversability of occluded floors. This study presents an innovative approachthat replaces first-person-view sensors with a third-person-view monocularcamera mounted on the observer robot. This approach can gather measurementsfrom multiple humans, expanding its range of applications. The key idea is touse two types of trackers, SLAM and MOT, to monitor stationary objects andmoving humans and assess their interactions. This method achieves stablepredictions of traversability even in challenging visual scenarios, such asocclusions, nonlinear perspectives, depth uncertainty, and intersectionsinvolving multiple humans. Additionally, we extend map quality metrics to applyto traversability maps, facilitating future research. We validate our proposedmethod through fusion and comparison with established techniques.

Walking = Traversable? : Traversability Prediction via Multiple Human Object Tracking under Occlusion