Easy Point Cloud OBJ Uploads! Instantly Share 3D Data in the Cloud

Table of Contents

• What is point cloud data?

• What is the OBJ format?

• Challenges in sharing point cloud data

• Benefits of sharing point cloud data in the cloud

• How to easily upload point cloud OBJ data

• What is LRTK? A point cloud surveying tool that works entirely on a smartphone

• Point cloud data sharing enabled by LRTK Cloud

• Benefits of introducing LRTK and use cases

• Simple surveying tools that excel on site

• Conclusion

• FAQ

What is point cloud data?

In construction and surveying, point cloud data (point cloud) refers to 3D data that represents the shape of objects or terrain as a collection of many points scattered across three-dimensional space. Each point records position coordinates (X, Y, Z), and depending on how it was captured, may also include attributes such as color information (RGB) or laser return intensity. Point clouds are obtained by measurements with laser scanners or LiDAR, or by reconstruction from images using photogrammetry, and are increasingly used across fields such as construction and civil engineering quality control and design verification, 3D documentation of cultural heritage, and environment perception for autonomous driving.

For example, on a construction site, scanning terrain and structures with lasers and converting them into point clouds allows creation of a detailed 3D model of the current conditions. Information that was traditionally shared only as plans or photos can be intuitively understood spatially using point clouds. Because of their precision and clarity, point clouds are valuable for tasks such as construction records, equipment management, and safety planning.

On the other hand, point cloud data is also characterized by being very large in data size due to its detail. High-density scans can consist of millions to hundreds of millions of points, and file sizes commonly reach hundreds of MB to several GB. Large-scale point clouds covering entire cities can even reach hundreds of GB. Because the data can become enormous, various issues arise when storing and sharing it. Next, let’s look at the representative file format OBJ format and the sharing challenges unique to point cloud data.

What is the OBJ format?

The OBJ format (.obj files) is one of the general-purpose file formats for recording 3D model geometry. Originally widely used to store polygon meshes (collections of vertices and faces) and material information, it is supported by many CAD programs and 3D viewers, making it an industry-standard exchange format for 3D data.

Although not a format dedicated to point clouds, point clouds can be meshed into vertex networks or exported as a list of vertices to an OBJ file. In practice, when you want to deliver laser-scanned point cloud data in a form that anyone can view, delivering it in a proprietary format may prevent recipients from opening it. A common solution is to convert the point cloud into a polygon (surface) model and export it as OBJ for sharing. Because OBJ files can be imported into common 3D software, the recipient can view the 3D scene without installing specialized viewers. For colored point clouds, providing an OBJ together with a material file (.mtl) and texture images allows sharing of color information as well.

Thus, the OBJ format is a highly versatile 3D data format, but because it is text-based it can become large. Converting a point cloud directly to OBJ can produce an enormous number of vertices, so it is advisable to downsample (reduce point density) or split the data as needed to create manageable file sizes. Free software such as CloudCompare and MeshLab is often used to convert point cloud data to OBJ. Using these tools, for example, LAS or PLY point clouds can be converted to OBJ files and used in game engines like Unity or web applications.

Challenges in sharing point cloud data

When attempting to share point cloud data with stakeholders, traditional methods face several difficulties. The main challenges include:

• Large file sizes: Point cloud data can become extremely large files, so uploading and downloading via cloud storage or attaching to emails can take a long time. With slow network connections, transfers can take hours, making it difficult to meet the need to share data immediately from the field.

• Specialized formats and viewers required: Point clouds are often saved in specialized formats such as LAS, PLY, or E57, and recipients need compatible software or dedicated viewers to open them. Advanced point cloud processing software can be expensive or difficult to use, so it’s not an environment that all stakeholders can easily use. Additionally, smoothly displaying and manipulating high-resolution point clouds may require high-performance PCs, meaning recipients with less capable devices may be unable to handle the data.

• Time lag between field and office: Traditionally, point cloud data captured in the field would be brought back to the office for processing and visualization on a PC before being distributed to stakeholders. This workflow makes it difficult to share the latest field conditions on site and creates a time lag between field personnel and the office.

• Difficulty of use: While point clouds enable intuitive 3D understanding, raw data delivered as-is does not make it easy for recipients to extract the information they need. Without the skills to view the 3D data properly or cut cross-sections, extracting required dimensions or shapes can be time-consuming. As a result, additional work such as re-creating 2D drawings or quantity tables tailored to the viewer is often necessary.

Given these challenges, there is demand for a way to smoothly share point cloud data in a form that anyone can easily handle. One promising solution is to upload point cloud data to the cloud and share a URL link that allows web-based viewing.

Benefits of sharing point cloud data in the cloud

Uploading point cloud data to the cloud and sharing it via the web offers many advantages. Even recipients who don’t have specialized software can view the same 3D data with just a URL link. The main benefits are:

• Viewable by anyone without specialized software: Clicking a shared link launches a point cloud viewer in the browser, allowing recipients to view the 3D data without installing special software. As long as they have a web browser, the data can be viewed on PCs, tablets, or smartphones. Because it doesn’t depend on the recipient’s environment, clients unfamiliar with 3D data or members of other departments can easily check it.

• Easy data distribution: Sharing a URL via email or chat is far simpler than distributing large point cloud files individually. If the latest data is always uploaded to the cloud, there is no need to send files to each stakeholder, and a centralized, up-to-date source is shared. This helps prevent mistakes like sending the wrong version or omitting recipients. Cloud storage also reduces risks like losing a USB drive or emailing the wrong file.

• No need for high-performance PCs: Because rendering and processing can be handled on the cloud side, recipients don’t need high-spec workstations to display 3D data smoothly. Previously, handling high-resolution point clouds required dedicated PCs, but viewing cloud-hosted data can be done on typical laptops or tablets. Online transfer also delivers data safely and quickly without physical media.

• Interactive collaboration: Cloud point cloud viewers often include collaboration features such as distance measurement and comment posting. Recipients can measure dimensions directly in the browser, mark points of interest, and provide feedback, enabling two-way information sharing. Unlike static drawings or reports, everyone can discuss while viewing the same 3D scene, reducing communication loss and making consensus-building smoother.

As described above, cloud-based point cloud sharing is extremely effective as a means to “distribute heavy 3D data easily and allow anyone to view it anywhere.” Next, let’s look at how to actually implement such a convenient sharing environment by uploading point cloud OBJ data easily.

How to easily upload point cloud OBJ data

Here is a practical workflow for sharing point cloud data using the cloud, summarized in four common steps.

• Check and prepare the data format: First, confirm the file format of the point cloud data you want to share. If your data is already in OBJ format, you can use it as-is. For LAS or PLY, convert to OBJ using the tools mentioned above (CloudCompare, MeshLab, etc.). If the file size is extremely large, consider splitting the data into regions or lowering resolution to make it easier to upload.

• Choose a cloud service: Select a cloud platform that supports point cloud data. Depending on your use case and security requirements, choose from specialized point cloud sharing services, general 3D model sharing sites, or an in-house cloud environment. Because services differ in supported formats, capacity limits, and features (such as measurement or commenting), check specifications in advance.

• Upload the data: Upload the prepared point cloud data (OBJ files) to the chosen platform. Typically, you specify files via a web browser upload screen or a dedicated app, and the cloud will ingest and process the data. Because point cloud files are large, use an office high-speed connection rather than a mobile network in the field, and avoid letting the PC sleep during upload. After upload completes, verify display in the cloud’s 3D viewer.

• Share the URL link: Once the data is published on the cloud, generate a share link (URL) for viewing. If the system can create a public URL per dataset, obtain that link and send it to intended recipients. Recipients can access the point cloud by clicking the URL in an email or chat. As noted above, no special software is required; viewers can freely move the viewpoint and take measurements in the 3D viewer, enabling all stakeholders to use the same data in real time.

Following these steps allows even very large point cloud data to be smoothly shared via the cloud, enabling immediate information sharing with relevant parties. The appeal is that with the right service, the process can be completed with drag-and-drop and URL distribution without complex settings or expert knowledge.

What is LRTK? A point cloud surveying tool that works entirely on a smartphone

To maximize the benefits of cloud sharing, it’s important to be able to easily capture high-quality point cloud data. Enter LRTK, a solution designed to let anyone perform high-precision point cloud measurements easily by combining a smartphone with a small GNSS receiver.

Specifically, a dedicated small GNSS device is attached to an iPhone or other smartphone and used in conjunction with the phone’s built-in LiDAR scanner. The GNSS receiver supports real-time kinematic (RTK) methods, enabling centimeter-level positioning accuracy (cm level accuracy (half-inch accuracy)) on a smartphone. By using that high-precision positioning information, absolute coordinates (world coordinates) can be assigned to the point clouds captured by the smartphone, allowing recording of 3D field information with accuracy comparable to conventional surveying. The ability to complete work that once required expensive laser scanners or dedicated equipment using only a smartphone and a palm-sized receiver is revolutionary.

The actual usage procedure is simple. Attach the LRTK device to the smartphone, start scanning with the dedicated app, and then walk around the area to be measured—the surrounding point cloud data is automatically captured. For example, scanning a medium-sized development site can be completed in about 5 minutes. No special操作s are required, and field workers can operate it intuitively without prior specialist training. The measurable range covers up to about 60 m (196.9 ft), capturing details from terrain to structures.

Furthermore, point cloud data obtained with LRTK can be output in formats that comply with public works quality control requirements. In other words, it’s not just scanning for its own sake—the data and accuracy can meet the standards for submission as results of public surveying. That the smartphone alone can capture such high-fidelity 3D data is LRTK’s major feature.

Point cloud data sharing enabled by LRTK Cloud

So how are point cloud data captured with LRTK shared in the cloud? The key is LRTK’s cloud integration. Once a scan is completed in the LRTK app on site, the data can be uploaded to the dedicated cloud with a single tap. On the cloud, the uploaded point cloud is automatically processed and stored, and users can access their data from office or home PCs as well as from their smartphones’ browsers.

Synchronized 3D data on the cloud can be used directly for browser-based measurement and analysis. The dedicated viewer allows one-click actions such as measuring distances and areas or cutting arbitrary cross-sections to display drawings. If you upload the point cloud captured on site to the cloud the same day, colleagues in the office can immediately open the data in their browsers to check the latest situation or measure required dimensions. A process that used to take days—from field capture to USB transfer back to the office and processing—can be completed with LRTK within the same day.

LRTK Cloud also provides the ability to issue share links (URLs) for each uploaded point cloud dataset. This allows you to show the same 3D point cloud data to external contractors or clients who do not have LRTK licenses or the app. Anyone who knows the share link can click the URL and open the point cloud viewer in their browser, reproducing virtually the same 3D view as the sender. No special equipment or software is required on the recipient side.

With this sharing link feature, it becomes much easier to, for example, present the latest construction status online to a client or consult with engineers at remote branches. Because the link lets anyone see the current state of the site, communication speed improves dramatically. Data is stored securely on the cloud, so there is no worry about losing USB drives or mixing up versions.

Benefits of introducing LRTK and use cases

Introducing LRTK on site brings significant advantages by streamlining the entire workflow from point cloud capture to sharing. Here are the main benefits and expected use cases.

• Rapid information sharing: Processes that used to take days to weeks—from on-site surveying to drawing creation and data sharing—can be completed the same day with LRTK. Synchronizing captured point clouds to the cloud and sharing via URL enables near-real-time information exchange between field and office.

• Cost and labor savings: Because measurements can be completed with only a smartphone and LRTK device, there is no need to rent large laser scanners or hire specialized surveying contractors. This reduces equipment transport and personnel coordination costs, enabling efficient surveying operations with limited staff. Sharing results via the cloud also reduces the distribution of paper drawings and USB handovers, easing data management overhead.

• Easy operation for anyone: The intuitive app interface allows users without specialist knowledge to operate it, so field workers themselves can capture and immediately share point clouds. There are reports of sites where LRTK was used effectively with no prior training for workers. Ease of use is a key factor in promoting ICT (digital) adoption on site.

• High accuracy and quality: Combining GNSS (RTK) with smartphone LiDAR ensures centimeter-level positioning accuracy (cm level accuracy (half-inch accuracy)) and high point density that captures detailed shapes. Using known control points for verification and correction can achieve quality comparable to conventional terrestrial laser scanner surveys. There are actual cases where LRTK data were used for public works quality measurements, demonstrating its reliability.

• Versatile utilization: Captured point clouds can be used in various ways on the cloud. For example, automatically generating mesh models (3D models) from point clouds allows comparison and verification with design data, or using AR features to overlay virtual completion images on site for confirmation. From measurement to advanced data utilization, LRTK’s cloud platform enables an integrated workflow.

By using LRTK, field-captured point cloud data can be quickly and multifacetedly utilized. Next, let’s look at LRTK use cases that are effective even for everyday minor measurement tasks.

Simple surveying tools that excel on site

So far we have discussed point cloud capture with LRTK and cloud sharing. But LRTK’s benefits on site go beyond that. LRTK excels at “simple surveying,” meaning it is powerful for ad hoc measurement tasks that arise suddenly in the field.

Consider a situation where you suddenly need a particular dimension on site. Traditionally, you would fetch a tape measure or call in a survey team, which takes time. With LRTK, you can simply scan the surroundings with a smartphone in hand and immediately obtain precise 3D data. Uploading to the cloud and measuring distances or areas lets you know the dimensions on the spot. Volume calculations for embankment or spoil can be done immediately on site, allowing instant updates to earthwork management and estimates.

LRTK also includes AR display features that utilize captured point clouds. For example, if the positions of buried pipes are recorded in a point cloud, you can view them in transparent overlay via your smartphone’s AR after paving to precisely know the locations of underground pipes. This helps plan safe excavation work that avoids buried utilities. In this way, LRTK supports a wide range of field tasks from simple measurements to advanced AR uses.

Conclusion

This article explained the solution of “uploading to the cloud and sharing” for the challenge of point cloud data sharing, and introduced LRTK as a tool that enables this workflow. Even very large and specialized point cloud data can be captured with a smartphone, uploaded to the cloud, and shared simply by sending a URL link using LRTK. Recipients can view 3D data without special software, dramatically improving internal and external information sharing efficiency.

LRTK transforms the time-consuming workflows of surveying, measurement, and data sharing. Turning necessary on-site information into 3D and sharing it immediately speeds up operations and accelerates consensus-building and decision-making among stakeholders. As an answer to the question “Easy point cloud OBJ uploads! Instantly share 3D data in the cloud,” LRTK is indeed one of the optimal solutions. If you are interested, why not try this new smartphone-based surveying workflow for yourself?

FAQ

Q: Is the cloud always required to share point cloud data? A: Traditionally, data could be exchanged using USB drives or external HDDs, but cloud usage is recommended for smooth sharing. In particular, LRTK includes cloud sync and URL sharing features as standard, enabling you to upload data and issue share links without extra steps. Using the cloud eliminates the need to copy huge files each time and provides the advantage of always being able to refer to the latest data online.

Q: How does a person who receives a share link view the point cloud data? A: It’s very simple. Clicking the sent URL automatically launches a point cloud viewer in the web browser and displays the 3D data. The recipient does not need to install special software. Using mouse or touch controls in the browser, they can rotate and zoom the point cloud, move the viewpoint freely, and inspect the 3D situation from various angles. Supported browsers allow viewing not only on PCs but also on smartphones and tablets.

Q: Can LRTK’s point cloud measurements be trusted for accuracy and quality? A: Yes, they can. LRTK combines high-precision GNSS (RTK method) with smartphone LiDAR, securing centimeter-level positioning accuracy (cm level accuracy (half-inch accuracy)) for the captured point clouds. Point density is also high, capturing shape details. Using known control points for correction enables quality comparable to conventional terrestrial laser scanner surveys. There are real cases where LRTK data were used for public works quality measurements, and its accuracy and reliability have been demonstrated.

Q: Can point cloud measurements really be done with only a smartphone? Is additional equipment unnecessary? A: LRTK is a solution composed of a smartphone and a dedicated GNSS receiver (and an app). The GNSS receiver is palm-sized and can be attached to the smartphone, giving the appearance and ease of measuring with just a smartphone. Technically, a small device attached to the phone is used, but no bulky tripods or laptops are required. All devices are battery-powered and operate cable-free in the field. High mobility makes it possible to measure point clouds in mountainous or high locations where bringing conventional equipment would be difficult.

Q: Can it be used offline? Can you capture and share point clouds in remote areas without cellular coverage? A: LRTK supports Japan’s satellite positioning services (the QZSS CLAS signals) and can achieve high-precision positioning even in areas without cellular coverage. Capturing point clouds on site does not require internet connectivity. Data captured offline can be uploaded to the cloud later when you move to an area with reception, and share links can then be issued. In other words, you can perform measurements in remote mountainous areas and later share them with stakeholders from the office.

Q: How can I introduce LRTK? A: LRTK is currently offered for the surveying and construction industries. If you are interested, contact LRTK’s official website or sales agents for details on introduction procedures, pricing, or demo requests. This new smartphone-based surveying method can deliver unprecedented efficiency. Please feel free to contact them.