Comprehensive Comparison of Browser-Compatible Point Cloud Viewers: New Generation Cloud-Based Tools and the Capabilities of LRTK

Table of Contents

• Introduction

• Background

• Feature Comparison

• Use Cases

• Expert Opinions

• Summary

• FAQ

Introduction

The use of point cloud data—point clouds—obtained by 3D scanners or photogrammetry is expanding in construction and surveying sites. However, displaying and sharing point clouds, which are vast collections of points, has traditionally been a high hurdle. This was because dedicated software installation or high-performance PCs were required. What has attracted attention is the cloud-based point cloud viewer that runs in a web browser. Recently, new-generation tools have emerged domestically and internationally that allow uploading point cloud data to the cloud via the Internet and viewing and analyzing them in a browser. In this article, we conduct a thorough comparison of browser-compatible point cloud viewers, examining each tool’s characteristics, usability, supported formats, shareability, analysis features, and more in detail. At the end of the article, from a third-party perspective we also introduce the point cloud viewer of "LRTK Cloud," which requires no installation, supports point clouds with absolute coordinates and AR integration, and can sync immediately from mobile devices, proposing it as a new entry point for simple field surveying and remote measurement.

Background

As advanced 3D measurement becomes more familiar, point cloud data has begun to be used routinely across a wide range of fields, including civil engineering, construction, and GIS. Because point clouds can digitize the real world at high accuracy, their applications have expanded to as-built verification, design validation, and infrastructure maintenance. At the same time, the image that "point clouds are difficult to handle" has persisted. The main reasons are as follows.

• Data volume and processing load: Because point cloud data are highly precise, the number of points can be extremely large, and file sizes tend to be huge. In some cases there may be millions to hundreds of millions of points, and scanning an entire city can produce data volumes reaching hundreds of GB. Previously, handling these required high-performance computers and large-capacity storage, and processing took a long time. It could take a long time to open data, and software could freeze—experiences like these led to the perception that "point clouds are hard to handle."

• Need for specialized equipment and software: In the past, measurement devices such as 3D laser scanners were very expensive and were affordable only to large companies or specialized vendors. Software for handling acquired point clouds was also specialized, and there were issues with conversion and compatibility with CAD and BIM tools. Multiple file formats (PLY, LAS, XYZ, etc.) exist, and data conversion and integration could be time-consuming. Barriers such as "we can't open it in our usual design software" or "we need to learn a new tool" discouraged adoption.

• Concerns about specialized knowledge: It was believed that advanced skills were required to process point clouds and operate 3D scanners. For example, extracting the necessary information from acquired point clouds once required know-how, including specialized processing steps like noise removal and coordinate transformation. For field personnel, psychological barriers such as "it looks difficult" or "isn't this only for experienced surveyors?" existed. There were also concerns about accuracy and whether point clouds could be integrated into existing workflows.

However, in recent years these hurdles have been rapidly lowering. Advances in cloud computing and web technologies (such as WebGL) have made it possible to process huge point cloud datasets on servers and render them smoothly in web browsers. The proliferation of drones and LiDAR-equipped smartphones has also reduced the cost of acquiring point clouds, creating an environment where anyone on site can capture and share 3D data. For example, devices like iPhones and iPads equipped with LiDAR sensors allow anyone to perform point cloud scans instantly using dedicated apps. Even without LiDAR, photogrammetry technologies that generate point clouds from photos have advanced, so point clouds are no longer confined to specialists. Against this backdrop, companies are developing cloud-complete point cloud viewers, and an era has arrived in which high-definition 3D point clouds can be handled with nothing more than a browser.

Feature Comparison

So what types of browser-compatible point cloud viewers are available, and what are their strengths? Below are representative types picked out for comparison from the perspectives of usability, supported data, sharing methods, analysis functions, supported devices, and so on.

| Type | Key features | Supported data formats | Sharing method | Main measurement & analysis functions | Supported devices/environment |

| --------------------------- | ----------------------------------------------- | ---------------------------------- | -------------------------------- | -------------------------------- | -------------------------- |

| Open-source type<br>(using WebGL libraries) | Free and customizable. Requires server setup and technical knowledge.<br>Flexible for integrating into in-house systems. | Standard point cloud formats like LAS/LAZ/PLY. | Published on your own web server.<br>Anyone can view via URL access (no authentication). | Distance measurement, cross-section display (area measurement possible depending on implementation). | PC browsers (high-performance GPU recommended).<br>Also works on mobile but with limits on displayed point counts. |

| International platform type<br>(offered by major vendors) | High-speed cloud processing for large point clouds. Can display integrated BIM/CAD data.<br>Usable from anywhere with an Internet connection. | Various scanner formats, standard point clouds like LAS/E57, design CAD/BIM models, etc. | Upload data to cloud project.<br>Share with stakeholders by inviting users (access control). | Distance, area, and volume measurements; coordinate checks; difference display between point clouds and design data; commenting. | PC browsers (can be used on general PCs).<br>May provide tablet viewers or companion apps. |

| Domestic integrated platform type<br>(for infrastructure and construction management) | Integrates not only point clouds but also drawing PDFs and photos.<br>Chat features and other tools smooth communication between field and remote teams. | In addition to point clouds like LAS/XYZ, supports images, drawings (PDF/DWG), etc. | Centralized data management in the cloud.<br>Stakeholders are issued IDs to log in, view, and comment. | Distance, cross-section, and angle measurement; comparison of temporal changes; linking photo notes.<br>Project-level chat and task management possible. | PC browsers (no special software required).<br>Viewable on tablets/smartphones (with limited functionality). |

| Mobile-integrated type<br>(smartphone measurement with cloud linkage) | Measurement by smartphone or drone → automatic cloud processing.<br>Point clouds are generated and shared in the cloud immediately after field capture. No installation required. | Photo data (automatically converted to point clouds), smartphone LiDAR point clouds.<br>Point cloud data that support absolute coordinates. | Cloud sync from the capture device and automatic sharing.<br>Viewable via URL or project share link. | Distance, area, and volume measurement; acquisition and export of point coordinates.<br>AR display using acquired point clouds (overlay in the real world). | PC browsers and smartphones/tablets.<br>(Can interoperate with mobile apps to leverage AR features) |

As shown above, point cloud viewers range from open-source freedom-focused solutions to high-functionality large cloud platforms, enterprise-integrated platforms, and mobile-focused solutions. Each has pros and cons. For example, open-source types have no initial licensing costs and can be customized to in-house needs, but setup and maintenance are your responsibility. Major platform types offer polished UIs and reliability but may require account registration and, in some cases, paid subscriptions. Domestic platform types provide field-oriented features (comparison with drawings and photos, chat-based instructions), but supported formats may be limited. Mobile-integrated types excel at on-site convenience and speed from capture to sharing, but often lack advanced editing features, so combining them with other tools may be desirable for detailed analysis. It is important to choose a viewer that matches your intended use and technical level.

Use Cases

In what specific situations do cloud-based point cloud viewers shine? Here are representative use cases in business operations.

• Streamlining as-built measurement and quantity calculation: When measuring excavation or fill volumes in earthworks, scanning the site and sending the data to the cloud can result in immediate volume calculations. For example, a task that previously took half a day from drone aerial photography to point cloud generation and mapping was completed on site in tens of minutes using tablet LiDAR scans. Because automatic measurement is available in cloud viewers, small-scale as-built management can be completed in about 30 minutes, directly reducing surveying effort.

• Remote site visits and progress sharing: Since multiple stakeholders can view the same point cloud data on the web while communicating, remote inspections and progress reporting become smoother. For example, if a disaster site’s point cloud is uploaded to the cloud, people can grasp the situation in 3D without visiting the site, issue instructions via chat, or add comments. There are reports that "thanks to 3D point clouds, the current situation was easier to understand than on 2D drawings," and recognition sharing between site and office has improved dramatically.

• Maintenance and difference analysis: In infrastructure inspections, overlaying past and latest point clouds to compare and detect changes or deterioration has become an established usage. Comparing time-series data in a browser point cloud viewer allows immediate understanding of terrain changes or structural displacements. In one prefecture, point clouds acquired before and after an earthquake were published so experts could analyze ground uplift in detail. Point cloud viewers are thus indispensable tools for building digital archives and creating digital twins.

From these use cases, cloud-based point cloud viewers demonstrate power across a wide range of scenarios, from field labor reduction to remote collaborative work and long-term asset management. Tasks that once relied on specialists can now be performed by field personnel themselves who can check and measure point clouds in a browser, transforming workflows.

Expert Opinions

Industry experts and field professionals generally view the new generation of point cloud viewers favorably. In one construction site, when the client was shared point cloud data through a viewer, they highly praised that "it was easier to grasp the current situation than with 2D drawings." Seeing is believing, and site professionals report that point cloud viewers enable all stakeholders to share the same three-dimensional situation, reducing misalignment of understanding.

From a developer’s perspective, an "intuitive UI that non-experts can operate easily" is emphasized. Features like writing comments as easily as chatting and the simplicity of viewing by opening a URL in a browser have made consensus building and progress management dramatically smoother. The ability to use cloud services without purchasing expensive dedicated software or hardware also lowers adoption barriers. Experts note that "the emergence of tools that are inexpensive to start with and easy for anyone to use is very significant."

Moreover, knowledgeable figures in point cloud technology say, "Point cloud data realize their true value as more people use them." With familiar devices like smartphones and drones capturing 3D data and cloud-based handling available to everyone, point clouds are becoming a common language on job sites rather than something special. There are voices that "point clouds are indispensable infrastructure for field records in the digital age," and browser-based point cloud viewers are expected to further strengthen their role as tools that promote DX (digital transformation).

Summary

We have reviewed browser-compatible point cloud viewers, from characteristics of various tools to application scenarios and expert opinions. The problems that used to plague point cloud data—heavy and difficult—can be addressed using cloud-complete viewers, enabling surprisingly easy visualization, sharing, and measurement. The key is choosing a tool that fits your organizational needs. For large projects, platforms with large-data handling and BIM integration are effective, while mobile-integrated types are attractive for small projects or speed-focused use.

Among tools gaining attention recently is the point cloud viewer of LRTK Cloud. This service generates point cloud models in the cloud from images or LiDAR scans taken with a smartphone and displays and measures them directly in a browser. By capturing with a dedicated app and syncing to the cloud, the point cloud is automatically uploaded to an installation-free 3D viewer. Because the acquired data include absolute coordinates based on site reference points, you can check world coordinates of arbitrary points in the browser and obtain survey results aligned to drawing coordinate systems. The viewer also features one-click switching to mobile AR mode to overlay point clouds onto the real world—useful, for example, for overlaying scanned buried objects to assist excavation planning. Tools like LRTK Cloud can be seen as a new entry point for simple surveying and measurement by field personnel. With user-friendliness that does not require specialized knowledge and the ease of cloud-based data sharing, such services have strong potential to become industry standard.

Thanks to the evolution of browser-compatible point cloud viewers, "using point cloud data" is beginning to shift from a special event to part of everyday work. Please use this article’s comparisons and explanations as a reference to choose the point cloud viewer that suits your operations. It can be the first step toward field DX and will improve operational efficiency and communication quality.

FAQ

Q: What is a point cloud viewer?

A: A point cloud viewer is software or a tool for visualizing three-dimensional point cloud data obtained by laser scanners or photogrammetry. It displays three-dimensional data composed of numerous points on a computer screen, allowing rotation, zooming, and inspection. Browser-compatible viewers enable point cloud viewing and simple analysis in a web browser without installing dedicated software. They typically do not perform complex point cloud processing (such as noise removal or modeling), but they make it easy to check the condition of produced point clouds, perform dimensional measurements, and share with others.

Q: What are the advantages of handling point clouds in a web browser?

A: The biggest advantages are ease of use and shareability. With a browser-based point cloud viewer, anyone can view 3D data simply by clicking an exchanged URL. Because no software installation is required, viewers do not need to prepare high-spec PCs or adjust settings. Since processing and hosting are done in the cloud, data are kept up to date and all stakeholders can access the same information. This reduces the work of repeatedly sending data from the site to the office, enabling point cloud data to be used "anytime, anywhere, by anyone."

Q: Can very large point cloud datasets be displayed?

A: Yes. Modern cloud-based point cloud viewers support large datasets. They use server-side spatial partitioning and LOD (level of detail) management and stream only the required area to the browser. Therefore, even massive datasets such as citywide laser scans can be viewed smoothly by limiting the display range. However, very slow network connections or extremely low-end viewer PCs can still cause long loading times. In general, with fiber-class network speeds and a standard WebGL-capable PC, large-scale point clouds stored in the cloud can be displayed and operated without problems.

Q: Is it safe to store point cloud data in the cloud?

A: Many cloud service providers implement robust security measures such as encrypted communications, access restrictions, and secure data centers. Some point cloud viewers allow setting access permissions per user and limiting viewers per project. Therefore, in general, it is safe to store and share data in the cloud. However, for highly confidential projects, it may be worth considering an on-premises deployment of an open-source viewer to isolate data from external access. Also, when using cloud services, review each provider’s terms of service and understand data ownership and handling before adoption.

Q: Can measurements of distance and area taken in a browser point cloud viewer be trusted?

A: Yes—if the point cloud data themselves are accurate, measurement results from a browser viewer are also accurate. Viewers essentially display point clouds and compute distances between coordinates, so they can produce results comparable to desktop software. Nevertheless, point clouds have inherent errors (scanner errors or photogrammetry inaccuracies), so when using measurements as official survey results, consider measurement conditions and error margins. For rough volume estimates and on-site dimensional checks, browser viewer measurements are sufficiently reliable. The crucial factors are the quality of the source data and correct scale and coordinate alignment in the viewer.

Q: Are there point cloud tools that beginners can use easily?

A: Yes. Recently, many beginner-friendly tools have appeared that do not require specialist knowledge. For example, smartphone-capture, cloud-complete point cloud services are simple to operate and recommended. Capture the site with a smartphone app and upload—the cloud automatically converts the photos to point clouds, and you can review the 3D model in a browser. Services like LRTK Cloud provide guided workflows from capture to sharing, making them easy even for first-time users. Because dedicated equipment is unnecessary, they are suitable for small-site checks or trial deployments. Starting with such tools and migrating to full-fledged platforms as needs grow is a practical way to progress in point cloud utilization.