TECHNICAL FIELD

The present disclosure relates generally to three-dimensional modeling of civil infrastructure, and more specifically to semantically labeling infrastructure.

BACKGROUND

Accurate and rapid assessment of the condition of in-service structural systems is critical for ensuring safety and serviceability. To this end, such structural systems are visually inspected to monitor condition over time.

Developments in the fields of remote sensing, robotics, nondestructive testing, sensors, and image capturing technologies provide an opportunity to collect large amounts of visual data such as images, videos, and three-dimensional (3D) imaging (also known as 3D point clouds or 3D meshes) along with non-visual data (e.g., field notes, sensor data, etc.) related to civil infrastructure that may be used to evaluate the condition of such systems. However, such a large amount disparate sources of data is not feasible to analyze and manipulate manually.

Some automated solutions exist. However, the existing solutions for visual data typically use two-dimensional images that have a narrow field and are often high-resolution close-ups of the structure. These images are fundamentally decontextualized since they do not consider the information in the context of the structure the way a human observer in the field intuitively does. In addition, a large amount of non-visual rich information on condition descriptors for infrastructure systems are underutilized, or are misunderstood due to a lack of comprehensive, correlated, and well-organized data structures. This results in an inability to integrate, fuse, georeference, analyze, and visualize these heterogeneous data sources.

As the amount of visual data increases, solutions for effectively storing that visual data become more important. Likewise, more related non-visual data is being collected. For example, such non-visual data may include annotations and measurements for items shown in visual content. Existing solutions face challenges in organizing the non-visual data appropriately.

It would therefore be advantageous to provide a solution that would overcome the challenges noted above.

SUMMARY

A summary of several example embodiments of the disclosure follows. This summary is provided for the convenience of the reader to provide a basic understanding of such embodiments and does not wholly define the breadth of the disclosure. This summary is not an extensive overview of all contemplated embodiments, and is intended to neither identify key or critical elements of all embodiments nor to delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more embodiments in a simplified form as a prelude to the more detailed description that is presented later. For convenience, the term “some embodiments” or “certain embodiments” may be used herein to refer to a single embodiment or multiple embodiments of the disclosure.

Certain embodiments disclosed herein include a method for three-dimensional asset modeling. The method comprises: initializing a georeferenced data structure for each of a plurality of discrete sub-regions of an asset based on a model representing the asset, wherein the model includes a plurality of points representing features of the asset, wherein each georeferenced data structure includes a subset of the plurality of points representing features of a respective sub-region of the plurality of sub-regions; and populating each georeferenced data structure with input data including three-dimensional (3D) modeling data and nonspatial data, wherein each portion of the input data for a georeferenced data structure is used to populate a respective portion of the georeferenced data structure, wherein the nonspatial data used to populate each georeferenced data structure is organized with respect to geometry of the georeferenced data structure and with respect to time of recording of the nonspatial data.

Certain embodiments disclosed herein also include a non-transitory computer readable medium having stored thereon causing a processing circuitry to execute a process, the process comprising: initializing a georeferenced data structure for each of a plurality of discrete sub-regions of an asset based on a model representing the asset, wherein the model includes a plurality of points representing features of the asset, wherein each georeferenced data structure includes a subset of the plurality of points representing features of a respective sub-region of the plurality of sub-regions; and populating each georeferenced data structure with input data including three-dimensional (3D) modeling data and nonspatial data, wherein each portion of the input data for a georeferenced data structure is used to populate a respective portion of the georeferenced data structure, wherein the nonspatial data used to populate each georeferenced data structure is organized with respect to geometry of the georeferenced data structure and with respect to time of recording of the nonspatial data.

Certain embodiments disclosed herein also include a system for three-dimensional asset modeling. The system comprises: a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to: initialize a georeferenced data structure for each of a plurality of discrete sub-regions of an asset based on a model representing the asset, wherein the model includes a plurality of points representing features of the asset, wherein each georeferenced data structure includes a subset of the plurality of points representing features of a respective sub-region of the plurality of sub-regions; and populate each georeferenced data structure with input data including three-dimensional (3D) modeling data and nonspatial data, wherein each portion of the input data for a georeferenced data structure is used to populate a respective portion of the georeferenced data structure, wherein the nonspatial data used to populate each georeferenced data structure is organized with respect to geometry of the georeferenced data structure and with respect to time of recording of the nonspatial data.

