Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (19): 57-69.DOI: 10.3778/j.issn.1002-8331.2105-0423

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Review on Semantic Segmentation of UAV Aerial Images

CHENG Qing, FAN Man, LI Yandong, ZHAO Yuan, LI Chenglong   

  1. College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, Sichuan 618307, China
  • Online:2021-10-01 Published:2021-09-29

无人机航拍图像语义分割研究综述

程擎,范满,李彦冬,赵远,李诚龙   

  1. 中国民用航空飞行学院 空中交通管理学院,四川 广汉 618307

Abstract:

With the rapid development of Unmanned Aerial Vehicle(UAV) technology, research institutions and industries have attached importance of UAV’s application. Optical images and videos are vital for the UAV to sense the environment, occupying an important position in UAV vision. As a hot spot of the current research of computer vision, semantic segmentation is widely investigated in the fields of unmanned driving and intelligent robot. Semantic segmentation of UAV aerial images is based on the UAV aerial image semantic segmentation technology to enable the UAV to work in complex scenes. First of all, a brief introduction to the semantic segmentation technology and the application development of UAV is given. Meanwhile, the relevant UAV aerial data sets, characteristics of aerial images and commonly used evaluation metrics for semantic segmentation are introduced. Secondly, according to the characteristics of UAV aerial images, it introduces the relevant semantic segmentation methods. In this section, analysis and comparison are made in three aspects including the small object detection, the real-time performance of the models and the multi-scale information integration. Finally, the related applications of semantic segmentation for UAV are reviewed, including line detection, the application of agriculture and building extraction, and analysis of the development trend and challenges in the future is made.

Key words: Unmanned Aerial Vehicle(UAV) imagery, semantic segmentation, computer vision, deep learning, convolution neural network

摘要:

随着无人机技术的快速发展,无人机在研究领域和工业应用方面受到了广泛的关注。图像和视频是无人机感知周围环境的重要途径。图像语义分割是计算机视觉领域的研究热点,在无人驾驶、智能机器人等场景中应用广泛。无人机航拍图像语义分割是在无人机航拍图像的基础上,运用语义分割技术使无人机获得场景目标智能感知能力。介绍了语义分割技术和无人机的应用发展、相关无人机航拍数据集、无人机航拍图像特点和常用语义分割评价指标。针对无人机航拍的特点介绍了相关语义分割方法,包括小目标、模型实时性和多尺度整合等方面。综述无人机语义分割相关应用,包括线检测、农业和建筑物提取等方向,并分析无人机语义分割未来发展趋势和挑战。

关键词: 无人机影像, 语义分割, 计算机视觉, 深度学习, 卷积神经网络