/ Column / Infrastructure Outlook: What’s New in Reality Capture?

Infrastructure Outlook: What’s New in Reality Capture?

Daniel Chapek on August 2, 2015 - in Column

New reality-capture technologies are gaining ground as firms realize that the flexibility offered by new tools can improve designs, reduce clashes and eliminate expensive site rework. Construction companies now use reality capture to monitor building projects as they’re constructed. Reality capture can answer the question “do the objects in real space match the design specification?”

Previously, it would take highly specialized scanners to capture images with enough precision to use as the basis of a design. Today, cellphones or cameras mounted on unmanned aerial vehicles (UAVs) can take photos good enough to turn into 3-D models for some applications. Although such photos don’t create a model as accurate as high-definition scanning, sometimes a less-detailed model will fit the bill. These two equipment trends are leading firms to look at how they might approach reality capture inhouse.

There’s an amazing array of technologies to choose from, and making decisions about which to acquire should be based on what’s needed from a business point of view. Just buying a UAV will not accomplish everything that’s required. In addition to the project’s capture phase, consider the processing and modeling phases. After data capture, tools are needed to make the data usable and beneficial—i.e., profitable!

Data Capture

The three primary high-tech ways to digitally capture terrain or built-environment information are 1) high-definition 3-D laser scanners, 2) mobile LiDAR systems (e.g., Leica’s Pegasus) and 3) digital cameras using photogrammetry software. UAVs have increased the speed of data collection, and they can carry cameras or an aerial LiDAR unit.

These scanning and photogrammetric methods result in a point cloud—a laser point cloud in the case of scanning and a photo point cloud in the case of photogrammetry. Although scanning can capture fine details such as material textures, the speed with which photogrammetry produces a point cloud is significantly faster.

So if you were planning to capture a mosque with a lot of tile inlay, then scanning would be better than photogrammetry. However, photogrammetry combined with LiDAR can produce powerfully accurate models, so it’s not always a case of cameras, mobile or stationary scanning as individual technologies. A firm can benefit from LiDAR and photogrammetry, depending on what it wants to achieve. The cost of high-definition scanning, although greater than camera-based capture, may be worth it, depending on the end product needed.

Processing

After data capture, technicians need to register the cloud to geocoordinates, and there are several different ways to achieve this. Scanner and photogrammetric camera manufacturers offer proprietary software to get data from hardware into digital formats. Independent software companies also offer post-capture processing with programs that recognize more than one format.

Many variables affect the capture and processing stages, so planning is imperative. The No. 1 question: what is the end deliverable? Will you be creating a terrain model? A detailed building information model (BIM)? A file for plant design? What type of data, at what resolution, do your projects require?

Resolution is an especially important question, because point-cloud files for high-resolution models are gigantic. Due to their size, they can swamp computing equipment and cause problems with file sharing and online collaboration. But don’t be fooled, a massive amount of data doesn’t always equate to inherent accuracies. Depending on the answers to these questions, you can “right-size” your gear. Maybe you don’t need a 36-megapixel camera, but you must have an HD scanner.

Modelling

After the point cloud has been registered to reference points, geometry-recognition software can help identify the points that make up trees, roof lines, pedestals or other structures. These tools create solid models, which designers then import into 3-D modeling programs.

Construction firms often use Navisworks for verification and inspection, because it allows engineers to compare the design against the built reality, post construction. In this case, surveyors can collect data using a Leica scanner, for example, and then register and process them with Cyclone. Then a design engineer can use Cloudworx for Navisworks to bring the point cloud directly into Navisworks for clash detection, without needing to import/export the data to shift file formats.

If technicians in the field used a Leica scanner to produce the point cloud and wanted to turn over a model for AutoCAD, they might use Cloudworx for AutoCAD, or they could use Autodesk ReCap 360. If creating a BIM-level deliverable, a product called Scan-to-BIM will extract models from a point cloud regardless of how the point cloud was brought into the Revit environment.

In spring 2015, Leica rolled out a new version of Cyclone as well as a new product called JetStream, which eliminates “wait times” long associated with point-cloud manipulation. It can be used with Cloudworx and enables continuous point importing, eliminating the requirement to refresh. Design engineers can import these files into AutoCAD, Revit or Navisworks using Cloudworx and share incredibly large datasets via the Web using TruView Global.

The key point is that depending on the final output, a firm should handpick different pieces of equipment and software. Working backward from the most typical deliverables, construction engineers can clarify which technologies work best together and which will net the biggest return on investment.

Daniel Chapek

About Daniel Chapek

Daniel Chapek is manager of reality-capture solutions for IMAGINiT Technologies, with more than a decade working with infrastructure technology.

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