U.M. Goyushova.
Determining the location of a moving device based on video images
The study is devoted to the development of an algorithm for the navigation of unmanned aerial vehicles based on video images, which requires less computational resources when comparing images taken at different times. Here, resource refers to the use of both time and memory space. In the proposed method, the images of the objects that the UAV can encounter are obtained from the Google Earth platform. Features are detected in images and a database of found features is created. The same features are detected in the images taken by the UAV during its movement. Current found features are compared with the features previously saved in the database. The location of the device is determined based on the coordinates of the object to which the features belong. The software of the algorithm is simulated in the C++ programming language and is intended to be used in onboard computers.
Keywords: UAV, Feature detection, Reference, Object recognition, Object detection
DOI: https://doi.org/10.54381/icp.2024.2.06
Determining the location of a moving device based on video images
The study is devoted to the development of an algorithm for the navigation of unmanned aerial vehicles based on video images, which requires less computational resources when comparing images taken at different times. Here, resource refers to the use of both time and memory space. In the proposed method, the images of the objects that the UAV can encounter are obtained from the Google Earth platform. Features are detected in images and a database of found features is created. The same features are detected in the images taken by the UAV during its movement. Current found features are compared with the features previously saved in the database. The location of the device is determined based on the coordinates of the object to which the features belong. The software of the algorithm is simulated in the C++ programming language and is intended to be used in onboard computers.
Keywords: UAV, Feature detection, Reference, Object recognition, Object detection
DOI: https://doi.org/10.54381/icp.2024.2.06