UAV-based panoramic scene recognition utilizing discrete spherical image features
Meng Liu, Yijie Ding, Yiyuan Xie · 2023
Vision scheme based on the unmanned aerial vehicle (UAV) has gained widespread attention in recent years. Nevertheless, on account of the limited field-of-view of traditional images, it is difficult to apply to the fields that require comprehensive visual information. Therefore, a novel visual scheme based on the UAV platform with panoramic images is proposed in this paper, in which a platform consists of the panoramic cameras and the unmanned aerial vehicle are innovatively established and a scene recognition method based on discrete spherical image features are implemented. For the sake of reducing the distortion of panoramic image, we propose an icosahedron-based panoramic image representation for feature extraction, and then combined with the convolutional neural network and support vector machine, recognition task of the real image captured by the UAV platform are accomplished. Compared with the most widely used representation, namely the equirectangular projection, the proposed method can improve the recognition accuracy by 13.64% based on the Panoramic Scene dataset. Besides, our method can obtain a better performance even under the condition of large noise. Therefore, the proposed UAV-based panoramic scene recognition method can be applied to the fields that require comprehensive visual information effectively.