Point Cloud OBJ Upload Complete Guide: Easily Share 3D Data in the Cloud

In construction and surveying sites, efficiently sharing 3D point cloud data is a major challenge. How can you easily upload bulky, specialized point cloud files to the cloud and share them with stakeholders? This article thoroughly explains the basics of point cloud data and the OBJ format, the problems with conventional sharing methods, and solutions using the cloud. We also provide step-by-step instructions for uploading and instantly sharing point cloud OBJ data to the cloud, and introduce the latest tool LRTK that enables easy point cloud measurement and sharing from a smartphone. Learn the secrets to smoothly sharing large 3D datasets using the cloud in this article.

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 via the cloud

• How to easily upload point cloud OBJ data

• What is LRTK? A smartphone-complete point cloud measurement tool

• Point cloud data sharing with LRTK Cloud

• Benefits of adopting LRTK and use cases

• Simple surveying tools that shine on site

• Conclusion

• FAQ

What is point cloud data?

First, “point cloud data” refers to 3D data that represents the shape of objects or terrain by placing many points in three-dimensional space. Each point records position coordinates (X, Y, Z), and depending on the acquisition method may also include attributes such as color information (RGB) or laser return intensity. Point clouds are acquired by laser scanners or LiDAR, or by reconstructing images via photogrammetry. They are increasingly used across many 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 you can create a detailed 3D model of existing conditions by laser-scanning terrain and structures and converting them to point clouds. Information that was previously shareable only as plans or photos can be intuitively understood in spatial terms using point clouds. Their precision and visual clarity provide great value in many situations such as construction records, equipment management, and safety planning.

On the other hand, point cloud data is characterized by being highly detailed and therefore very large in size. High-density scans can range from millions to hundreds of millions of points, and file sizes commonly reach from several hundred MB to several GB. Large-scale point clouds that cover an entire city can amount to several hundred GB. Because data becomes so huge, various challenges arise when storing and sharing it. Next, let’s look at the representative 3D data file format OBJ and the specific sharing challenges of point cloud data.

What is the OBJ format?

The OBJ format (.obj) is a common file format for recording 3D model geometry. Originally used widely for saving polygon meshes (collections of vertices and faces) and material information, it is supported by many CAD programs and 3D viewers, and is considered an industry-standard 3D data exchange format.

OBJ is not a format dedicated to point clouds, but you can mesh a set of vertices that make up a point cloud or export just the vertex list as an OBJ file. In practice, if you want to deliver laser-scanned point clouds in a form that anyone can view, the raw specialized formats may be unreadable by recipients. A common solution is to convert point clouds into polygon (surface) models and export them as OBJ files for sharing. Exporting to OBJ allows recipients to import and view the 3D scene using general 3D software without installing specialized viewers. If the point cloud includes color, you can also provide a material file (.mtl) and texture images along with the OBJ to share color information.

While OBJ is very versatile, its text-based nature means it can easily become large in file size. Converting point clouds directly to OBJ can produce a massive number of vertices, so it’s advisable to reduce density (decimation) or split the data as needed to make file sizes manageable. Free tools like CloudCompare and MeshLab are commonly used to convert point cloud formats (LAS, PLY, etc.) to OBJ. Using these tools, you can convert LAS or PLY point clouds to OBJ and then use them in game engines (such as Unity) or web applications.

Challenges in sharing point cloud data

When sharing point cloud data with stakeholders, conventional methods encounter several difficulties. The main challenges include:

• Heavy files: Point cloud files are very large, so attaching them to emails is impractical, and even uploading or downloading via cloud storage can take a long time. On slow networks, transfers can take hours, preventing immediate sharing from the field.

• Specialized formats and viewers required: Point clouds are often saved in specialized formats such as LAS, PLY, or E57, requiring recipients to install compatible software or dedicated viewers. Advanced point cloud processing software can be expensive or difficult to use, so not everyone can easily access it. Additionally, smoothly displaying and manipulating high-resolution point clouds may require a high-performance PC; recipients with limited hardware may be unable to handle the data.

• Time lag between field and office: Traditionally, point clouds captured on site are taken back to the office for processing and visualization on a PC before being distributed to stakeholders. This workflow makes it hard to instantly share the latest field conditions, causing a time lag in information sharing between field staff and office personnel.

• Difficulty of use: Although point clouds allow intuitive 3D understanding, raw data alone does not make it easy for recipients to extract needed information. Without skills to open the data in an appropriate viewer, navigate views, or cut sections, extracting dimensions or shapes can be cumbersome. As a result, additional work such as creating 2D drawings or quantity tables tailored for viewers often becomes necessary.

Given these issues, a method that enables point cloud data to be smoothly shared in a form everyone can handle is needed. One promising solution is to upload point cloud data to the cloud and share a URL that allows web-based viewing.

Benefits of sharing point cloud data via the cloud

Uploading point cloud data to the cloud and sharing it via the web offers many advantages. Recipients can view the same 3D data with a single URL link even if they don’t have specialized software. The main benefits are:

• No special software required; anyone can view: Clicking the shared link launches a browser-based point cloud viewer, so recipients can view 3D data without installing special software. As long as they have a web browser, they can view it from a PC, tablet, or smartphone. This cross-platform accessibility enables customers or colleagues not familiar with 3D to easily check the data.

• Easy distribution: Sending a single URL via email or chat is far simpler than distributing enormous point cloud files individually. If the latest data is always uploaded to the cloud, there is no need to send files to each stakeholder every time—the cloud provides centralized, up-to-date information. This prevents version confusion or missing recipients, and cloud storage reduces risks like lost USB drives or mis-sent emails.

• No need for high-performance PCs: Rendering and processing of point clouds are done on the cloud side, so recipients don’t need high-spec workstations to smoothly view 3D data. Previously, handling high-resolution point clouds required dedicated PCs, but viewing cloud-hosted data can be done on a typical laptop or tablet. Sending data from the field to the office online is also safer and faster than using physical media.

• Interactive collaboration: Cloud-based point cloud viewers often include collaboration features like distance measurement and comments. Recipients can measure dimensions in the browser, mark points of interest, and provide feedback—enabling two-way information sharing. Unlike static drawings or reports, everyone can discuss while looking at the same 3D space, reducing communication loss and speeding consensus.

As described, cloud-based point cloud sharing is an effective way to “distribute heavy 3D data easily and allow anyone to view it anywhere.” So how can you practically create such a convenient sharing environment? Next, let’s look at how to easily upload and share point cloud OBJ data.

How to easily upload point cloud OBJ data

Here is a practical workflow for cloud-based point cloud sharing, summarized in four general steps.

• Confirm and prepare data format: First confirm the file format of the point cloud you want to share. If your data is already in OBJ format, you can use it as-is. If it’s in another format such as LAS or PLY, convert it to OBJ using the aforementioned tools (CloudCompare, MeshLab, etc.). If the file size is extremely large, split the data by regions or decimate points to reduce resolution and make uploads more manageable.

• Choose a cloud service: Select a cloud platform that can handle point cloud data. Depending on your needs and security requirements, consider specialized point cloud sharing services, general 3D model sharing sites, or a company’s private cloud environment. Since services vary in supported formats, capacity limits, and features (such as measurement/comment functions), check specifications in advance.

• Upload the data: Upload your prepared point cloud data (OBJ file) to your chosen platform. Typically, you select the file via a browser upload screen or dedicated app, and the cloud performs ingestion and conversion for display. Because point clouds can be large, it’s best to use an office high-speed network rather than a mobile connection when possible, and prevent the PC from sleeping during upload. After uploading, verify that the cloud 3D viewer displays the data correctly.

• Share the URL link: Once the data is uploaded to the cloud, generate a shareable link (URL) for viewing. If the system can generate a public URL per dataset, obtain it and send it to intended recipients. Recipients can click the URL in an email or chat to access the point cloud in a browser. As noted earlier, no special software is required, and users can freely change viewpoints and take measurements in the 3D viewer, allowing all stakeholders to use the same data in near real time.

Following these steps lets you smoothly share even very large point cloud datasets via the cloud, enabling instant 3D information sharing with necessary parties. The simplicity—often as easy as drag & drop plus sending a URL—makes it feasible without complex setup or expert knowledge.

What is LRTK? A smartphone-complete point cloud measurement tool

To fully leverage cloud sharing, it’s important to first be able to easily acquire high-quality point cloud data. Enter LRTK, a solution designed to enable anyone to perform high-precision point cloud measurements by combining a smartphone with a compact GNSS receiver.

Specifically, a dedicated ultra-compact 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) operation, achieving centimeter-level (half-inch) positioning accuracy even with a smartphone. By using this high-precision position information, absolute coordinates (world coordinates) can be assigned to the point cloud captured by the phone, enabling on-site 3D data recording with accuracy comparable to conventional surveying. The ability to complete tasks that previously required expensive laser scanners or specialized equipment using just a smartphone and a palm-sized receiver is revolutionary.

The actual usage procedure is simple. Attach the LRTK device to your phone, start scanning with the dedicated app, and walk around the area you want to measure—the surrounding point cloud data is automatically captured. For example, a medium-sized earthworks site can be scanned in about 5 minutes. No special operation is required, and field workers can use it intuitively without prior specialized training. The capture range extends to a radius of approximately 60 m (196.9 ft), enabling detailed capture of terrain and structures.

Moreover, point clouds obtained with LRTK can be output in formats compliant with public works quality control guidelines. In other words, it’s not just scanning—the data and accuracy are suitable for submission as public survey deliverables. The ability to acquire such high-resolution 3D data using only a smartphone is LRTK’s most significant feature.

Point cloud data sharing with LRTK Cloud

How do you share point cloud data acquired with LRTK in the cloud? The key is LRTK’s cloud integration feature. After completing a scan in the LRTK app on site, you can upload the data to the dedicated cloud with a single tap. On the cloud, uploaded point clouds are automatically processed and stored, and users can access their data from office or home PCs as well as from the smartphone’s browser.

Synchronized 3D data on the cloud can be used directly in a browser for measurement and analysis. The dedicated viewer allows you to measure distances and areas, cut arbitrary cross-sections and display them as drawings, and perform other advanced visualizations with a click. If you upload point clouds captured on site to the cloud the same day, colleagues in the office can immediately open the data in a browser, verify the latest conditions, and take necessary measurements. What used to take days to bring data back from the field, process it, and share it can be completed with LRTK within the same day.

LRTK Cloud also provides a feature to generate shareable 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 apps. Anyone with the shareable link can click the URL, launch the browser-based point cloud viewer, and see almost the same 3D view as the sender. No special equipment or software is required on the recipient’s side.

With this link feature, it becomes much easier to, for example, explain the latest construction status online to a project owner or consult a remote branch’s engineer about site conditions. Sharing the “now” of the site with anyone via a link dramatically speeds up communication. The data is securely stored on the cloud, eliminating concerns such as lost USB drives or version mismatches.

Benefits of adopting LRTK and use cases

Adopting LRTK on site streamlines the entire workflow from point cloud acquisition to sharing. Key benefits and expected use cases include:

• Rapid information sharing: Processes that once took days to weeks—from field surveying to drawing production and data sharing—can be completed the same day with LRTK. Sync point clouds to the cloud and share URLs to enable near-real-time information exchange between field and office.

• Cost and labor savings: Measurements are completed with just a smartphone and the LRTK device, eliminating the need to rent large laser scanners or hire specialized surveyors. This reduces transport and staffing costs and allows efficient surveying with limited personnel. Cloud-based sharing also cuts down on paper plans and USB exchanges, reducing data management effort.

• Easy operation for anyone: Intuitive app operation makes it usable without specialized knowledge, allowing field workers to capture and immediately share point clouds themselves. There are reported cases where workers used LRTK effectively without prior training. Ease of use is crucial for promoting ICT (digital) adoption on sites.

• High accuracy and quality: Combining GNSS (RTK) with smartphone LiDAR yields centimeter-level (half-inch) positional accuracy and high point density that captures fine shape details. Further correction with known reference points can achieve quality comparable to conventional terrestrial laser scanning. LRTK-obtained data has been used in public works quality control, demonstrating its accuracy and reliability.

• Versatile applications: Captured point clouds can be used in various ways on the cloud platform—automatically generating mesh models (3D models) for comparison with design data, using AR to overlay virtual completion images on-site, and more. The ability to complete everything from measurement to data utilization on LRTK’s cloud platform is a significant advantage.

Using LRTK lets you swiftly and flexibly leverage point cloud data captured on site. Next, let’s look at LRTK use cases where simple surveys on the jobsite are especially effective.

Simple surveying tools that shine on site

So far we’ve discussed point cloud acquisition and cloud sharing with LRTK, but LRTK’s advantages extend further. LRTK excels at “simple surveying,” meaning quick ad-hoc measurements that occur spontaneously on site.

For example, imagine you suddenly need a dimension on site. Traditionally you might fetch a tape or call a specialized survey team, which takes time. With LRTK you can scan the surroundings with one hand holding a smartphone and instantly obtain precise 3D point cloud data. Uploading to the cloud and measuring distances or areas allows you to immediately get the dimensions you need on site. Calculating volumes of embankment or excavated soil can be done on the spot, enabling immediate updates to earthwork management or estimates.

LRTK also includes AR display features that leverage captured point cloud data. For example, you can record the positions of underground pipes in a point cloud and then, after paving, view them through the smartphone AR to see the exact positions under the ground. This allows safer planning for future excavation by knowing the locations of buried utilities in advance. In this way, LRTK supports a wide range of field operations—from quick everyday measurements to advanced AR applications.

Conclusion

This article explained the solution of “uploading point cloud data to the cloud and sharing it” and introduced LRTK as a tool that makes this possible. Even very large and specialized point cloud datasets can be captured with a smartphone, uploaded to the cloud with LRTK, and shared with stakeholders simply by sending a URL. Recipients can view the 3D data without installing software, dramatically improving information sharing both inside and outside your organization.

LRTK transforms the time-consuming workflows of surveying and point cloud sharing. Being able to instantly convert required on-site information into 3D and share it not only speeds operations but also accelerates consensus building and decision-making among stakeholders. As one answer to the theme of “easily uploading point cloud OBJ data and sharing 3D data in the cloud,” LRTK is an optimal solution. If you are interested, consider trying this new smartphone-based surveying workflow.

FAQ

Q: Is the cloud absolutely necessary to share point cloud data? A: Traditionally, data was exchanged via USB drives or external HDDs, but for smooth sharing the cloud is recommended. LRTK includes cloud sync and URL sharing as standard features, allowing you to upload and publish share links without extra steps. Using the cloud avoids repeatedly copying huge files and lets everyone reference the latest data online.

Q: How does someone view point cloud data from a shared link? A: It’s very simple. Click the sent URL and a browser-based point cloud viewer automatically launches, displaying the 3D data. The recipient does not need to install special software. In the browser they can rotate, zoom, and move viewpoints with mouse or touch to inspect the 3D scene from various angles. Supported browsers allow viewing from PCs as well as smartphones and tablets.

Q: Is the accuracy and quality of LRTK’s point cloud measurement reliable? A: Yes. LRTK combines high-precision GNSS (RTK) positioning with smartphone LiDAR, achieving centimeter-level (half-inch) positional accuracy. The point density is high and captures detailed shapes. With optional correction using known reference points, the quality can match conventional terrestrial laser scanning. LRTK-acquired data has been used in public works quality control, demonstrating its accuracy and reliability.

Q: Can you really measure point clouds with only a smartphone? Are large additional instruments unnecessary? A: LRTK is a solution consisting of a smartphone, a dedicated GNSS receiver, and a dedicated app. The GNSS receiver is palm-sized and attaches to the phone, so it feels like measuring with just a phone. Strictly speaking, you attach a small device to the phone, but no large tripods or laptops are required. All components have built-in batteries and operate cablelessly, offering high mobility. This makes measurements feasible even in mountainous or elevated locations where transporting conventional equipment is difficult.

Q: Can it be used offline? Can you capture and share point clouds in remote areas with no signal? A: Yes. LRTK supports Japan’s satellite positioning service (the CLAS signal from Michibiki), enabling high-precision positioning even where mobile signals are unavailable. Capturing point cloud data itself works offline. Data collected offline can be uploaded to the cloud later after moving to a location with connectivity, at which point you can generate share links. In other words, you can measure in remote areas and share the data with stakeholders once you return to a place with a connection.

Q: How do I adopt LRTK? A: LRTK is currently offered for the surveying and construction industries. Interested parties can contact LRTK’s official website or authorized dealers for details on adoption, pricing, and demo requests. By using this smartphone-based surveying method, you can experience unprecedented efficiency—feel free to contact them for more information.