Bed occupancy detection using geometric features from point clouds

Abstract

Embodiments described herein provide systems and techniques for detecting hospital bed occupancy based on three-dimensional (3D) point clouds of the hospital bed extracted from depth images. In one aspect, a process for determining if a bed inside an operating room (OR) is occupied by a patient is disclosed. This process begins by receiving a 3D point cloud of a bed object within a depth image captured inside the OR. The process then segments the 3D point cloud of the bed object into a plurality of segments in both a length direction and a width direction of the bed object. Next, the process extracts a set of geometric features from the plurality of segments. The process subsequently applies a binary classifier to the set of geometric features to classify the bed object as either being occupied by a patient or not being occupied by a patient.