A NEW COARSE-TO-FINE STRATEGY FOR BRIDGE-OVER-WATER DETECTION

Bridge-over-water detection plays vital role in both civilian and military applications. Though widely studied previously, it is still a challenging problem. This is because bridges are with a high diversity of aspect ratios, shapes and orientations in practical. The detection performance is highly dependent on the annotation accuracy of training samples. To address these problems, this paper proposes a new coarse-to-fine strategy to detect oriented bridges over water. In coarse detection stage, a new backbone containing modulated deformable convolution is developed to enrich the diversity of receptive fields. The detection results are further refined by the prior knowledge. The oriented bounding boxes can be then obtained based on frequency domain analysis and edge detection. Different from previous works, oriented bounding box annotaions are not required in the training of the proposed method. Comparative experiments were conducted. The results demonstrate the effectiveness of the proposed method.