An Artificial Intelligence (AI) roof deterioration analysis system that tracks changes in roofs over time by evaluating a series of features in high-resolution images.

A system and method for the measurement of distances related to an object depicted in an image. One aspect including delivery of supplemental materials for fenestration and for constructing insulating materials for fenestration. A digital image containing a primary object dimension and a reference object dimension in substantially the same plane undergoes digital image processing to provide improved measurement capability. Information regarding a primary object is provided to an automated measurement process, design and manufacturing system to provide customized parts to end users. A digital image is obtained having an observable constraint dimension to which a customized part is to conform wherein the digital image contains a reference object having a reference dimension and a constraint dimension is calculated from the digital image based on a reference dimension. The custom part is designed and manufactured based on the calculated constraint dimension.

Methods, systems, and computer code on computer-readable media are provided that are directed to generating area skyline data using a digital elevation or surface models (DEMs or DESs) and shadow casting techniques. Some embodiments use an area of maximum shadow line overlap, for shadow line images based on target location skyline azimuth and elevation angle data, as the best approximation for the position of the target location in an area. Some embodiments select the location showing the best fit to the target skyline azimuth and elevation angle data as the best approximation for the target location.

A system for utilizing object tracking algorithms for tracking objects external to a vehicle includes a processor and a memory in communication with the processor. The object tracking algorithms include a lower computationally demanding object tracking algorithm and a higher computationally demanding object tracking algorithm. The memory has one or more modules that have instructions that cause the processor to determine if the vehicle is located in an urban setting or a non-urban setting and utilize the lower computationally demanding object tracking algorithm by an object tracking system when the vehicle is located in the non-urban setting. If it is determined that the vehicle is in an urban setting, the instructions cause the processor to determine available computational resources of the object tracking system and utilizing either the lower computationally demanding object tracking algorithm or the higher computationally demanding object tracking algorithm based on the available computational resources.

Systems, apparatuses, and methods are provided for developing a fingerprint database and selecting feature geometries for determining the geographic location of a device. A device collects a depth map at a location in a path network. Two-dimensional feature geometries from the depth map are extracted using a processor of the device. The extracted feature geometries are ranked to provide ranking values for the extracted feature geometries. A portion of the extracted feature geometries are selected based upon the ranking values and a geographic distribution of the extracted feature geometries.

An image processing method and an image processing device detect an object from a driving image of a vehicle, obtain information on an altitude difference between the vehicle and the object, and input image domain coordinates of the object in the driving image and the information on the altitude difference to a neural network and determine world domain coordinates of the object.

A system for utilizing object tracking algorithms for tracking objects external to a vehicle includes a processor and a memory in communication with the processor. The object tracking algorithms include a lower computationally demanding object tracking algorithm and a higher computationally demanding object tracking algorithm. The memory has one or more modules that have instructions that cause the processor to determine if the vehicle is located in an urban setting or a non-urban setting and utilize the lower computationally demanding object tracking algorithm by an object tracking system when the vehicle is located in the non-urban setting. If it is determined that the vehicle is in an urban setting, the instructions cause the processor to determine available computational resources of the object tracking system and utilizing either the lower computationally demanding object tracking algorithm or the higher computationally demanding object tracking algorithm based on the available computational resources.

Methods, systems, and computer code on computer-readable media are provided that are directed to generating area skyline data using a digital elevation or surface models (DEMs or DESs) and shadow casting techniques. Some embodiments use an area of maximum shadow line overlap, for shadow line images based on target location skyline azimuth and elevation angle data, as the best approximation for the position of the target location in an area. Some embodiments select the location showing the best fit to the target skyline azimuth and elevation angle data as the best approximation for the target location.

A method, apparatus and computer program product identify objects of interest within images. In a method, the method receives one or more images generated by an image capture device that is configured to be relocated. The method also receives information regarding an estimated location of the image capture device. Based upon a representation of a respective image of the one or more images and respective representations of a plurality of reference images, the method identifies one or more reference images that are associated with the estimated location. The method also identifies an object of interest within the respective image generated by the image capture device based upon respective digital signatures of one or more objects of interest and at least some context associated with the one or more objects of interest that are depicted by the one or more reference images that have been identified.

A method, apparatus and computer program product train a signature encoding module and a query processing module. In a method, at least one of the signature encoding module and the query processing module is trained by providing the signature encoding module with a reference image containing a particular object of interest that is marked therewithin. The method generates a digital signature of the object of interest and at least some context associated therewith and provides the query processing module with a query image and the digital signature representing the object of interest and at least some of the context associated therewith. The method additionally identifies the object of interest within the query image based upon the digital signature and modifies at least one of the signature encoding module or the query processing module based upon a qualitative or quantitative difference between the objects of interest identified within the query image and marked in the reference image.