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首页> 外文会议>International Seminar on Intelligent Technology and Its Applications >Inclined Image Recognition for Aerial Mapping by Unmanned Aerial Vehicles
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Inclined Image Recognition for Aerial Mapping by Unmanned Aerial Vehicles

机译：无人机空中制图的倾斜图像识别

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摘要

In general, aerial mapping is an image registration problem, i.e., the problem of transforming different sets of images into one coordinate system. Aerial mapping is one of the important capability of an unmanned aerial vehicle (UAV). Here, the images processed by the registration system is strongly influenced by the quality of the image captured by the UAV. To select the image that will be processed efficiently is not easy considering the ground truth in the mapping process is not given before the UAV flies and captures the image. On the other hand, generally, UAV will fly and take the image in sequence regardless of the quality. These will result in several issues, such as: 1) the quality of mapping results becomes bad, and 2) the computational cost of registration process becomes high. To tackle such issues, therefore, we need a recognition system that is able to recognize images that should be excluded from the registration process. In this paper, we define such image as an “inclined image,” i.e., images captured by UAV not perpendicular with the ground. Although we can calculate the inclination angle using a gyroscope attached to the UAV, our interest here is to recognize the images without the use of such sensor like human do. To realize that, we utilize a deep learning method to build an inclined image recognition system. We tested our proposed system with images captured by UAV. The results showed that the proposed system yielded accuracy rate of 86.4%.
机译：通常，空中映射是图像配准问题，即，将不同的图像集转换为一个坐标系的问题。空中制图是无人飞行器（UAV）的重要功能之一。在此，由配准系统处理的图像受UAV捕获的图像质量的强烈影响。考虑到在无人机飞行并捕获图像之前未给出制图过程中的地面真相，选择要进行有效处理的图像并不容易。另一方面，无论质量如何，无人机通常都会按顺序飞行并拍摄图像。这些将导致几个问题，例如：1）映射结果的质量变差，并且2）注册过程的计算成本变高。因此，为了解决这些问题，我们需要一个识别系统，该系统能够识别应从注册过程中排除的图像。在本文中，我们将此类图像定义为“倾斜图像”，即由无人机捕获的不垂直于地面的图像。尽管我们可以使用安装在无人机上的陀螺仪来计算倾斜角度，但我们的兴趣是无需像人类一样使用这种传感器来识别图像。为了实现这一点，我们利用深度学习方法来构建倾斜的图像识别系统。我们用无人机捕获的图像测试了我们提出的系统。结果表明，所提系统的准确率为86.4％。

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