Detection and Reconstruction of Wires Using Cameras for Aircraft Safety Systems

We extend the ability of cameras to perceive obstacles for aircraft safety systems by enabling 3d sensing of free hanging wires. Our algorithm exploits the specialized 2d and 3d structure of wires to exceed state of the art performance in 2d sensing and 3d location estimation of wire obstacles. In 2d, a new neural network architecture, Deep Wire CNN, directly predicts the location of wire line segments in the image. In 3d, the detections are tracked and triangulated as the aircraft flies in order to estimate the wire’s location. Our triangulation uses a new formulation of wire reconstruction as the estimation of the wire’s vertical plane. Together these advancements enable real-time detections of wire hazards at ranges of over 1km. The system performance is evaluated on prior image level wire detection datasets and we introduce a new public dataset in order to evaluate full system results on over 40 approaches to power lines from a manned helicopter.