Toward the automatic detection of access holes in disaster rubble

The collapse of buildings and other structures in heavily populated areas often result in multiple human victims becoming trapped within the resulting rubble. This rubble is often unstable, difficult to traverse and dangerous for first responders who are tasked with finding and extricating victims through access holes in the rubble. Recent work in scene mapping and reconstruction using RGB-D data collected by unmanned aerial vehicles (UAVs) suggest the possibility of automatically identifying potential access holes into the interior of rubble. This capability would allow critical limited search capacity to be concentrated in areas where potential access holes can be verified as useful entry points. In this paper, we present a system to automatically identify access holes in rubble. Our investigation begins with defining a hole in terms of its functionality as a potential means for accessing the interior of rubble. From this definition, we propose a set of discriminative geometric and photometric features to detect “access holes”. We conducted experiments using RGB-D data collected over several disaster training facilities using a UAV. Our empirical evaluation indicates the potential of the proposed approach for successfully identifying access holes in disaster rubble scenes.