In variants, the method for occlusion correction can include: determining a measurement depicting an occluded object of interest (OOI), optionally infilling the occluded portion of the object of interest within the measurement, and determining an attribute of the object of interest based on the infilled measurement.

A system includes one or more cameras configured to attach to an aircraft and capture a plurality of images. The plurality of images includes a first image including a runway and a subsequently captured second image including the runway. The system includes an aircraft computing system configured to identify common features in the first and second images, determine changes in locations of the common features between the first and second images, and determine a predicted landing location of the aircraft in the second image based on the changes in locations of the common features. The aircraft computing system is configured to abort landing on the runway based on the predicted landing location relative to the runway.

A computing system including an edge computing device. The edge computing device may include an edge device processor configured to receive edge device contextual data including computing resource availability data. Based at least in part on the edge device contextual data, the edge device processor may select a processing stage machine learning model of a plurality of processing stage machine learning models and construct a runtime processing pipeline of one or more runtime processing stages including the processing stage machine learning model. The edge device processor may receive a runtime input, and, at the runtime processing pipeline, generate a runtime output based at least in part on the runtime input. The edge device processor may generate runtime pipeline metadata that indicates the one or more runtime processing stages included in the runtime processing pipeline. The edge device processor may output the runtime output and the runtime pipeline metadata.

A system determines spatial locations of pixels of an image. The system includes a processor configured to: receive location data from devices located within a hotspot; generate a density map for the hotspot including density pixels associated with spatial locations defined by the location data, each density pixel having a value indicating an amount of location data received from an associated spatial location; match the density pixels of the density map to at least a portion of the pixels of the image; and determine spatial locations of the at least a portion of the pixels of the image based on the spatial locations of the matching density pixels of the density map. In some embodiments, the image and density map are converted to edge maps, and a convolution is applied to the edge maps to match the density map to the pixels of the image.

Determining GPS coordinates of some image point(s) positions in at least two images using a processor configured by program instructions. Receiving position information of some of the positions where an image capture device captured an image. Determining geometry by triangulating various registration objects in the images. Determining GPS coordinates of the image point(s) positions in at least one of the images. Saving GPS coordinates to memory. This system and method may be used to determine GPS coordinates of objects in an image.

The present application discloses a method and apparatus for determining a route, a device and a computer storage medium, and relates to the field of big data. An implementation includes: acquiring route description information input by a user, and acquiring a route contour with the route description information; matching the route contour in road network data to obtain the route matched with the route contour, so as to generate recommended routes, wherein this operation specifically includes: extracting intersection points in the route contour, each of which is formed by intersecting at least two lines; selecting one of the intersection points, and querying the road network data using a corresponding angle sequence of the selected intersection point in the route contour, so as to obtain intersections matched with the selected intersection point as candidate intersections; traversing the candidate intersections, fixedly mapping the selected intersection point to the positions of the candidate intersections, equally scaling the route contour in the road network data, and recording mapped road information if all lines of the route contour are mapped onto connected roads; and generating the recommended routes with the recorded road information.

An apparatus for analyzing a payload being transported in a load carrying container of a vehicle is disclosed. The apparatus includes a camera disposed to successively capture images of vehicles traversing a field of view of the camera. The apparatus also includes at least one processor in communication with the camera, the at least one processor being operably configured to select at least one image from the successively captured images in response to a likelihood of a vehicle and load carrying container being within the field of view in the at least one image, and image data associated with the least one image meeting a suitability criterion for further processing. The further processing includes causing the at least one processor to process the selected image to identify a payload region of interest within the image and to generate a payload analysis within the identified payload region of interest based the image data associated with the least one image.

Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

A high-precision waterway reconstruction method based on a multi-satellite source information coupling is provided. The method includes a determination method for a waterway section, a reconstruction method for a basic waterway section high-precision coupling, a reconstruction method for a fixed waterway section coupling, and a reconstruction method for a river reach waterway terrain. The method fills the gap of surveying and mapping of the waterways based on satellite remote sensing information, extremely improves the perpendicular precision and planar precision of the existing digital surface model of satellites for river waterways, and provides decision support for a water-related emergency rescue in areas lacking data.

The method for generating a road edge line includes: acquiring a road image; recognizing lane line information from the road image; recognizing key point information related to the road edge from the road image; and generating the road edge line according to the lane line information and the key point information.