# FAQ

## How does photogrammetry work?

Photogrammetry refers to methods that derive three-dimensional information from (two-dimensional) photos or videos. The method is called triangulation. From at least two positions, the same point is targeted. This allows the determination of the 3D coordinates of the point. The problem is solved mathematically by placing a spatial transformation between the pixel on the camera sensor and the physical point. The formula is: [x y z] = R * [X Y Z] + C. [x y z] is the pixel position on the sensor, where z is the focal length. R is the rotation matrix of the camera that describes the camera's angular orientation. [X Y Z] is the spatial position of the point. C is the camera's position in the room. This equation is determined for all points, slightly reshaped and made into a linear system of equations by linearization. The only known input parameters are the coordinates of the measuring point on the sensor. All other parameters like camera position and point position are calculated. In practice, the formula described above is extended to include so-called distortion parameters which describe the distortion of the image by the camera, in particular by the lens. The distortion manifests itself, for example, in that straight lines are slightly bent in the image. The most important distortion parameter is the radial symmetric distortion. The resulting system of equations often has 5000 unknowns and tens of thousands of equations. It is solved by the least squares method. The whole procedure is called bundle block adjustment. This process is the gold standard for precision applications and is of course included in all Linearis3D products. The basis for this 3D calculation is the knowledge of the coordinates of the point to be measured on the sensor. For precision applications, self-adhesive or magnetic circles with a black edge have proven themselves. Their center can be detected very fast and with an accuracy of 0.03! pixels or better. For non-industrial applications, it is also possible to use striking points such as color transitions, corners and edges, which are often not available in sufficient numbers in the industrial environment.## Where does the photogrammetry come from?

The classic photogrammetry comes from cartography. From aerial photos maps were created. For this application special, particularly stable large format analog cameras and evaluation devices have been developed. With the start of digital cameras, so-called close-range photogrammetry has gained in importance, capturing objects that are between 10cm and 50m in size.## How accurate is photogrammetry?

For photogrammetric systems operating with a single hand-held camera, the accuracy is evaluated according to the guideline VDI 2634. Photogrammetry can achieve maximum length deviations of less than 0.03mm in 1m^{3}according to VDI 2634. The results depend on the object, the software and the camera. When comparing photogrammetry systems, you should pay attention which standard was used to determine the accuracy. Sometimes so-called RMS (root mean squared) deviations are used, which result in much smaller values for the same physical error. For video systems with two cameras, the accuracy is about 0.1mm/m

^{3}.

## What are the advantages of short-range photogrammetry?

- Photogrammetry is robust against shocks. Forklift traffic and pressing do not affect the measurement results as long as the object does not deform in itself.
- You can measure in tight spaces (e.g., vehicle interior).
- Photogrammetry is very economical due to the inexpensive hardware.
- The operating costs are low, since the consumables (markers) are very cheap.
- Photogrammetry can efficiently detect deformation states with any number of measurement points.

## Is photogrammetry complicated?

No. Although the mathematics behind it is complex, everyone can learn the application in a short time. The Linearis3D software calculates the results automatically and gives advice for improvement.## Why do Linearis3D uses markers?

- Markers accelerate image analysis
- The centers of the markers can be detected very precisely (up to 1 / 30px) and allow highly accurate 3D measurement results
- Markers work for almost all objects and environmental conditions.

## Can photogrammetry operate without markers?

Yes. There are programs that work with so-called feature points. These recognize distinctive points in images and can assign them. The method proves itself, e.g., in architecture. Technical objects are often monotonous and there are often too few feature points in order to be able to operate photogrammetry.## What role does the camera play for accuracy?

The camera plays a minor role. Especially important is the lens as well as the stability of camera and lens. Therefore, small zoom cameras are not well suited for photogrammetry.## What are the advantages of photogrammetry towards laser tracker?

- Photogrammetry is robust against shocks. Forklift traffic and pressing do not affect the measurement results as long as the object does not deform in itself.
- You can measure in tight spaces.
- The acquisition costs are significantly lower.
- The photogrammetry can efficiently detect deformation states with any number of measurement points.

## What are the advantages of photogrammetry towards a measurement arm?

- Photogrammetry is robust against shocks. Forklift traffic and pressing do not affect the measurement results as long as the object does not deform in itself.
- You can measure in tight spaces.
- The measurement objects can have any size.
- The photogrammetry can efficiently detect deformation states with any number of measurement points.

## How can photogrammetry work together with a scanner?

Photogrammetry can significantly improve the accuracy of multiple-scan scans by providing the scanner with a reference system consisting of markers. This is very helpful especially for large, smooth-surfaced objects like cars. Linearis3D supports export formats of all major scanner manufacturers.## Where can I learn more about photogrammetry?

- Luhmann, Thomas: Nahbereichsphotogrammetrie, Wichmann, Heidelberg, 3. Auflage
- Luhman, Thomas: Erweiterte Verfahren zur geometrischen Kamerakalibrierung in der Nahbereichsphotogrammetrie. DGK, München, 2010.