Frequently Asked Questions

What is LiDAR?

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses lasers to scan an environment or infrastructure. It can be either static or mounted on a vehicle such as a car, train, or drone (known as Mobile Mapping System or MMS). By emitting laser beams and measuring the time it takes for them to bounce back, LiDAR creates a point cloud - a precise numerical copy of the scanned area. This technology has become increasingly affordable and is widely used today in various sectors, including surveying, mapping, and engineering.

What is a point cloud?

A point cloud is a digital representation of an environment or infrastructure that is created by using lasers to scan and capture millions of precise 3D points. This process is named LiDAR acquisition. It is essentially a numerical copy of the scanned area that enables us to make accurate measurements and inspections as if we were on the field. With the increasing availability and affordability of LiDAR technology, creating point clouds has become much easier and more widespread.

While a point cloud contains a wealth of information, to make it useful, it needs to be processed. This can involve classifying the objects within the point cloud, vectorizing polylines, and other advanced processings for complex applications. At TheCrossProduct, we specialize in processing point clouds to extract valuable information that can be used for various professional applications.

What is point cloud classification? How to classify a point cloud? What is the use of point cloud classification?

Point cloud classification is the process of assigning a category to each point in the cloud, allowing for object recognition and segmentation. It is crucial for extracting relevant information from the cloud and realizing business applications. Usually, classification can be done manually, or assisted by convenient tools or by a trainable AI. Manual/assisted classification can be slow and imprecise, while trainable AI requires proper training and configuration. However TheCrossProduct offers a turnkey solution which is an automated classification method specific to each business need, thus no need for any training or user intervention.
For a deeper dive into this subject, we invite you to check out our blog post at Point Cloud Classification Article

What is point cloud vectorization? How to modelize a point cloud? What are the best tools to vectorize polylines?

Point cloud vectorization is a process of drawing lines from the 3D points in a LiDAR-scanned area. It is an essential step for the analysis of the cloud and the development of calculations. Once polylines are obtained through vectorization, they can be used to complete GIS and BIM models of infrastructures, automate measurements, carry out reverse engineering studies of road or rail geometry, or can be used for advanced professional applications such as clash detection. Vectorization can be done manually, but this method can be long and tedious. An alternative is automatic vectorization using software such as TheCrossProduct's Railway Automated Vectorization. This software solution combines artificial intelligence, deterministic algorithms, and specific business knowledge to provide fast, reliable, and precise results.
To learn more about this topic, we've written an informative blog article that you can access via Point Cloud Vectorization Article  

How to realize professional applications thanks to point clouds ?

Point clouds carry a wealth of information and are very useful for a lot of applications. However this raw data is hard to use without specialized tools. The process typically involves classification and vectorization to identify relevant objects within the data. Once extracted, automated computations can be performed on specific objects of interest. These computations enable various measurements such as safety distance analysis or the simulation of virtual gauges to check for potential collisions. By harnessing the power of point clouds, these professional applications facilitate fast and accurate analysis in a range of industries.

What is the difference between BIM and GIS?

BIM, or Building Information Modeling, is a local 3D model that is used for designing, constructing, and managing buildings and infrastructure projects. It provides detailed information about the physical and functional characteristics of a structure, such as its geometry, materials, and systems. On the other hand, GIS, or Geographic Information System, is a global management system that integrates geographic data, such as maps and satellite imagery, with other data sources to analyze and manage all types of infrastructure, including buildings, roads, and utilities. While BIM and GIS have different purposes, they are often used together to provide a more comprehensive understanding of a project or location. 

What is the best process to do "scan to BIM"?

Scan to BIM is the process of creating a BIM model from 3D laser scans of an existing structure. The best process to do scan to BIM involves several steps, including data acquisition, registration, segmentation, modeling, and quality control. Data acquisition involves capturing high-resolution scans of the physical structure, while registration involves aligning and merging the individual scans into a single point cloud. Segmentation involves separating the point cloud into meaningful objects or components, while modeling involves creating a 3D BIM model from the segmented objects. Quality control ensures that the model accurately represents the physical structure and meets the necessary standards and requirements. The scan to BIM process can be time-consuming and complex, but it provides a detailed and accurate representation of an existing structure that can be used for renovation, maintenance, or construction projects.

How to visualize a point cloud? What are the best tools for point cloud visualization?

There are two primary methods to visualize a point cloud:

1) Using desktop software: If you already have the point clouds stored on your computer or a drive, desktop software is a convenient option. However, it may not be ideal for sharing data visualization with your colleagues, and weaker computers may struggle to handle large point clouds. One example of desktop software is CloudCompare, which is a highly regarded free viewer compatible with Windows and Linux operating systems.

2) Utilizing a cloud platform: A cloud platform offers a user-friendly approach to point cloud visualization, as it only requires a web browser. These platforms are designed to handle large point clouds effortlessly and enable easy sharing of views and annotations with your team. An example of such a platform is Geo-Cassini.

Consider your specific needs and preferences to determine the best method for visualizing your point clouds. Desktop software may be suitable for individual use or smaller projects, while a cloud platform offers the advantages of easy collaboration and scalability for larger-scale projects.

How to choose between desktop software and SaaS software for point cloud processing?

Choosing between desktop software and SaaS software for point cloud processing depends on various factors, such as the size and complexity of the data, the processing requirements, and the user's budget and expertise. While desktop software may have been the traditional solution for point cloud processing, SaaS software offers several advantages. SaaS software is accessible from any browser, requires no installation or powerful machine, and provides fast and precise processing using extremely powerful algorithms running on supercomputers in the cloud. Additionally, SaaS software can be more cost-effective and scalable than desktop software, as users only pay for the resources they use.

What are the advantages of automated processing?

Automated processing of point clouds offers several advantages over manual processing. Automated processing is faster, more reliable, and time-saving, allowing users to focus on other tasks. Additionally, automated processing is more precise and accurate than manual processing, as it reduces the risk of human error and inconsistencies. By automating point cloud processing, users can increase productivity, reduce costs, and improve the overall quality of their work.

How do TheCrossProduct solutions work?

TheCrossProduct solutions use cloud processing to handle point cloud data. Users can upload their point clouds to the cloud, and the processing starts automatically. The algorithms run on supercomputers in the cloud then process the data, such as classification, modeling or professional applications. Once the processing is complete, users can retrieve the processed data as well as several reports and use them in their project. TheCrossProduct solutions provide a fast, reliable, and cost-effective way to process point cloud data without requiring any specialized hardware or software. Finally, these solutions can also be used through an API in order to be efficiently integrated in the processing chain of the client. This API can also be used to integrate the solution in cloud based platforms. 

Can you develop specific features?

TheCrossProduct has a highly talented team, including PhDs who enjoy solving new challenges. Do not hesitate to contact us to discuss your specific needs, so we will determine if new features can be added to our roadmap.

What is the price of your solutions?

We offer flexible pricing options for our solutions. Users can choose between a per km billing model or an annual license for recurrent needs. We aim to provide cost-effective solutions that allow users to process their point cloud data efficiently and affordably. Especially, our tools are highly scalable and well-suited for large-scale projects that span thousands of kilometers, thus we propose degressive pricing for such needs.



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