A Novel Algorithmic Framework for Standoff Concealed Threat Detection
The HIVE algorithmic framework enables new approaches to protecting people and infrastructure in areas where traditional security checkpoints are not feasible. HIVE (Hierarchical Inference for Volumetric Estimation) is a custom deep convolutional neural network architecture that interprets volumetric video generated by a standoff, active-RF imagers. The architecture performs multi-resolution detection, classification, and segmentation of objects in the scene at various scales in order to produce automated threat detections, alerts, and visualization products – all without requiring the person to stop, pose, or remove their belongings.