Combined Convolutional And Structured Features For Power Line Detection In Uav Images

Power line detection plays an important role in automated UAV inspection system, which is crucial for real-time motion planning and navigation along power lines. Previous methods which adopt traditional filters and gradients may fail to capture complete power lines due to noisy background. To overcome this, we develop an accurate power line detection method using rich convolutional and structured features. The proposed method fully exploits multiscale and structured prior information to conduct both accurate and efficient detection. We evaluate the method on two well-annotated power line datasets and achieve state-of-the-art performance compared with previous methods.