The present invention relates to a method and system for facilitating access to recorded data. The system comprises an interface and a processing device. The interface is arranged to receive data and the processing device is arranged to separate the received data in data subsets, compress each data subset and assign an identifier to each compressed data subset, thereby creating data units each comprising a compressed data subset and an associated identifier, the processing device further being arranged to establish an index on the basis of the assigned identifiers.

An automated structural feature and analysis system is disclosed. A 3D device emits a volume scanning 3D beam that scans a structure to generate 3D data that is associated with a distance between the 3D device and each end point of the 3D beam positioned on the structure. An imaging device captures an image of the structure to generate image data with the structure as depicted by the image of the structure. A controller fuses the 3D data of the structure generated by the 3D device with the image data of the structure generated by the imaging device to determine the distance between the 3D device and each end point of the 3D beam positioned on the structure and to determine a distance between each point on the image. The controller generates a sketch image of the structure that is displayed to the user.

A photograph of a component after construction is acquired. A first program implemented on a communication terminal device displays a construction photograph solicitation icon soliciting a construction photograph on a display panel, when there is a component without the construction photograph in a first database stored in a memory of a second server. When accepting a selection of the construction photograph solicitation icon, the first program launches an imaging program and acquires photograph data. Alternatively, the first program acquires photograph data selected from a folder. The first program sends the acquired photograph data to the second server through a first server. A third program of the second server registers the sent photograph data in a second database. An operator selects one photograph from photographs shown by a plurality pieces of photograph data registered in the second database, and registers the photograph data of the selected photograph in the first database.

Systems and methods for automated detection of changes in extent of structures using imagery are disclosed, including a non-transitory computer readable medium storing computer executable code that when executed by a processor cause the processor to: align, with an image classifier model, an outline of a structure at a first instance of time to pixels within an image depicting the structure captured at a second instance of time; assess a degree of alignment between the outline and the pixels depicting the structure, so as to classify similarities between the structure depicted within the pixels of the image and the outline using a machine learning model to generate an alignment confidence score; and determine an existence of a change in the structure based upon the alignment confidence score indicating a level of confidence below a predetermined threshold level of confidence that the outline and the pixels within the image are aligned.

In variants, the method for property condition analysis can include: determining a measurement, optionally determining a set of property attributes, determining a condition score, optionally providing the condition score, and optionally training a condition scoring model.

A few-shot urban remote sensing image information extraction method based on meta learning and attention includes building a few-shot urban remote sensing information pre-trained model. During a pre-training stage, pre-training network learning is performed for a few-shot set to fully learn feature information of existing samples and obtain initial feature parameters and a deep convolutional network backbone of the few-shot set; the few-shot urban remote sensing information pre-trained model is a network structure including a convolutional layer, a pooling layer and a fully-connected layer, and includes five sections of convolutional network where each section includes two or three convolutional layers, and an end of each section is connected to one maximum pooling layer to reduce a size of a picture; the number of convolutional kernels inside each section is same, and when closer to the fully-connected layer, the number of convolutional kernels is larger.

A method, apparatus, and computer program product are provided for using aerial imagery to identify and distinguish fluid leaks from objects, structures, and shadows in aerial imagery. A method may include: receiving an aerial image of a geographic region; identifying objects within the aerial image; determining shadow areas associated with the objects within the aerial image; determining whether areas exist contiguous with the shadow areas and extending beyond the shadow areas; identifying one or more fluid leaks in response to areas existing contiguous with the shadow areas and extending beyond the shadow areas; and generating an indication of the one or more fluid leaks including one or more locations of the one or more fluid leaks.

The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.

A method, an apparatus and an electronic device for processing point cloud data and a computer readable storage medium are disclosed. The method includes: receiving first point cloud data acquired by a laser scanner; classifying the first point cloud data to obtain second point cloud data which is classified; judging if the second point cloud data at least comprises target point cloud data, and whether a distance between other point cloud data in the second point cloud data and the target point cloud data is smaller than a first preset threshold value; if yes, determining the other point cloud data as hazardous point cloud data.

A method and system for improving damage assessment by automatic measurement of virtual objects within an augmented reality (AR) representation of a physical environment are disclosed. A user interacts with a mobile computing device to position and resize virtual objects within a virtual space corresponding to a physical environment, which is presented to the user as an AR environment generated by the mobile computing device. The virtual objects are positioned and sized to match damaged physical objects within the physical environment. The sizes of the physical objects are automatically determined using the virtual sizes of the virtual objects, which physical sizes are further used to determine the extent of damage.