Abstract: Systems and methods may include tracking one or a plurality features across a decreasing scale of tiled sets of one or more images. Aspects may include generating point data for each of the tracked features based on a coordinate system relative to the first camera or the second camera, and transforming the point data to a Global Positioning System/Inertial Navigation System (GPS/INS) coordinate system based on (1) an origin of a first GPS device coupled to the first camera and (2) a rotation of the first camera relative to an INS device coupled to the first camera. Aspects may include generating, based on the transformed point data, a geodetic mapping function, determining, based on the geodetic mapping function, georegistered coordinates of the tracked features, using the georegistered coordinates of the tracked features to characterize the water flow.

Abstract: Embodiments relate to characterizing a water flow. Initially, a camera targeted at the water flow obtains images. An image pyramid is generated for each image, and a first level of each image pyramid is tiled at an initial scale to identify initial features. The initial features are matched across the first level of the image pyramids at a pixel-level to obtain a first set of feature displacements. A second level of each image pyramid is tiled at a decreased scale to identify a scaled set of features. The scaled features are matched across the second level of the image pyramids at the pixel-level to obtain a second set of feature displacements. Optical flow algorithms are applied to modify each feature displacement to account for a corresponding subpixel registration. A stereo reconstruction is applied to the feature displacements to generate a three dimensional (3D) displacement map.

Abstract: Embodiments relate to characterizing a water flow. Initially, a camera targeted at the water flow obtains images. An image pyramid is generated for each image, and a first level of each image pyramid is tiled at an initial scale to identify initial features. The initial features are matched across the first level of the image pyramids at a pixel-level to obtain a first set of feature displacements. A second level of each image pyramid is tiled at a decreased scale to identify a scaled set of features. The scaled features are matched across the second level of the image pyramids at the pixel-level to obtain a second set of feature displacements. Optical flow algorithms are applied to modify each feature displacement to account for a corresponding subpixel registration. A stereo reconstruction is applied to the feature displacements to generate a three dimensional (3D) displacement map.