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We often get asked, "How accurate is the 3D model I can create using Elios 2 visual data?" While the answer isn't straightforward, it's crucial to understand that the accuracy of your 3D model heavily depends on the precision of the data used to construct it.
Generally speaking, the maximum accuracy achievable for a 3D model built from visual data captured by the Elios 2 is three times the Ground Sampling Distance (GSD), which refers to the size of the pixels as they appear on the model's surface. With the Elios 2's 4K camera, you can achieve a GSD of 0.25mm/pixel, leading to a theoretical maximum accuracy of around 0.75mm. However, for simplicity, we usually round this up to 1mm.
Take a look at this video demonstrating how to achieve such accuracy by incorporating reference dimensions near the objects being measured:
[Embedded YouTube Video]
A few key aspects of the model showcased in the video include:
- It was filmed under ideal conditions: no backlight, on a non-reflective surface, and with plenty of texture.
- The area modeled was relatively small (approximately 0.5 m²) to measure small objects (<5cm).
- Two scale constraints and one orientation constraint were set across the area.
- Test measurements were conducted close to the scale constraints.
- The model wasn't referenced to any specific coordinate system, focusing instead on relative accuracy.
It's important to note that while achieving 1mm accuracy with the Elios 2 is possible, it may not always be necessary or practical for every project. Your desired level of accuracy should align with the purpose of your 3D model. If pinpoint accuracy is required—say, determining the precise distance between two parts of an object—you'll need to plan meticulously, fly close to the object, and gather high-quality data. Conversely, if you're simply looking for a general understanding of spatial relationships, you can save time and effort by flying further away.
Remember, the quality and accuracy of your 3D model depend directly on the quality and accuracy of the data you collect. Here are some tips for ensuring optimal accuracy:
- Larger areas require more reference points (known as "scale constraints" in Pix4D). The bigger the area, the more reference points you'll need, and the larger the reference dimensions should be.
- Proximity to the object matters. The closer you can get, the better the accuracy.
- Lighting plays a critical role. Dust and poor lighting can degrade image quality, affecting your 3D model.
- Calibration ensures smooth drone flights and clear images.
- Reflective surfaces pose challenges due to their lack of distinct features.
[Image of large space photogrammetry]
Ground Sampling Distance (GSD) is another critical factor. GSD measures the distance between the centers of two adjacent pixels on the object being imaged, typically expressed in mm/px. A GSD of 1mm/px indicates that one pixel represents 1mm in reality. Unlike pixel resolution, GSD improves as the camera gets closer to the object, offering greater detail and visibility of smaller features.
[Image showing 3D model accuracy example]
Photogrammetry is inherently scale-related. The closer you can get to the object, the more accurate your map will be. The Elios 2’s unique cage design allows it to fly close to objects, making it an excellent tool for high-quality data collection. In the video mentioned earlier, the Elios 2 flew just 20 cm (7.8 inches) from the surface.
Keep in mind, though, that choosing the right GSD should align with your project’s needs. There’s always a trade-off between accuracy and efficiency. High accuracy demands closer proximity and more time, while lower accuracy allows for quicker coverage over larger areas.
Fun fact: The Elios 2 can capture images with a GSD of 0.18 mm/px when flying at a distance of 30 cm (11.8 in).
Three key resolutions to consider are pixel resolution, GSD resolution, and spatial resolution. Learn more about how the Elios 2 performs across these metrics.
[Image of photogrammetry 3D model]
When using a fisheye lens, GSD also depends on the object's position within the image, not just the distance from the camera. Objects in the center of the image will have a smaller GSD, appearing larger, while those in the corners will have a higher GSD, appearing smaller.
The intended use case significantly influences accuracy requirements. For instance, land surveys require less precision compared to indoor inspections, where understanding the exact location of bolts or welds relative to doorways or other features is crucial.
[Case Study: Elios 2 Tested for Indoor Stockpile Volumetry]
For example, if you're inspecting a 500mm duct to locate defects, you'd want to ensure that workers can access the area accurately identified by your 3D model.
Planning your mission with the end-use in mind is vital. Whether you're aiming for high accuracy for detailed inspections or broader coverage for less critical tasks, the Elios 2 offers versatile capabilities.
To delve deeper into photogrammetry with the Elios 2, check out these resources:
- [Webinar] Indoor 3D Modeling Use Cases: Photogrammetry in Action
- [Webinar] Indoor 3D Modeling: Applications & Implications
- [Article] Why use photogrammetry to build 3D models of indoor spaces
- [Article] Building 3D models with Elios 2: How to acquire appropriate data for photogrammetry
- [Article] Building 3D models with Elios 2: Processing data with a photogrammetry software
These resources can help you optimize your workflow and achieve the best results with the Elios 2.
June 20, 2025