Abstract: A computer that includes a processor and a memory, the memory includes instructions executable by the processor to estimate a relative rotation between a ground view image and an aerial view image with a rotation estimator. A ground feature map and a confidence map corresponding to the ground view image are projected to an aerial feature map corresponding to the aerial view image according to the relative rotation to create a projected overhead-view feature map. A translation difference is determined between the projected overhead-view feature map and the aerial feature map using spatial correlation. A high-definition estimated three degree-of-freedom pose of a ground view camera is determined based on the relative rotation and the translation difference.

Abstract: A computer includes a processor and a memory, and the memory stores instructions executable by the processor to generate an observed overhead feature map from an overhead image of a geographic area; generate a ground-view feature map from a ground-view image captured by a camera within the geographic area, the camera oriented at least partially horizontally while capturing the ground-view image; project the ground-view feature map to an overhead view based on a geometric relationship, resulting in a projected overhead feature map; determine a rotation of the camera relative to the overhead image based on the projected overhead feature map and the observed overhead feature map; and determine a translation of the camera relative to the overhead image based on the projected overhead feature map and the observed overhead feature map.

Abstract: A computer that includes a processor and a memory, the memory including instructions executable by the processor to determine a first feature map and a first confidence map from a ground view image with a first neural network. First feature points can be determined based on the first feature map and the confidence map. First three-dimensional (3D) feature locations of the first features can be determined based on the first features and the first confidence map. A second feature map and a second confidence map can be determined from an aerial-view image with a second neural network. Second 3D feature locations can be based on the first 3D features, the second feature map and the second confidence map. A three degree-of-freedom (DoF) pose of a ground view camera in global coordinates can be determined by iteratively determining geometric correspondence between the first and second 3D feature locations.

Abstract: The disclosure discloses a soil moisture monitoring system. The soil moisture monitoring system comprises a high-frequency signal source, for providing a soil moisture detection high-frequency signal; a sensing unit, comprising multiple nodes of sensing components arranged at intervals and in a layered manner and for sensing moisture of soil profiles at different depths under the action of the high-frequency signal source; a signal detection circuit, connected with the sensing unit and for generating a first voltage signal and a second voltage signal separately under the action of the high-frequency signal source; and a time division multiplexing switching unit, arranged between the sensing unit and the signal detection circuit and for conducting the sensing component in each layer and the signal detection circuit in a time division manner.