Method and means for scaling and orienting in photogrammetric analysis

Abstract

There is provided a 3D object for a 3D measurement. The 3D object comprises 1D markers and at least one 2D scale bar comprising a predefined distance between at least two 1D markers. The 3D object comprises at least three planes, of which at least one comprises a 2D scale bar and the at least two comprise at least two 1D markers both, wherein the at least three planes are non-parallel with each other. The 3D object comprises an equipment configured to determine orientation of the 3D object.

Description

[0001] Method and means for scaling and orienting in photogrammetric analysis

[0002] Field of invention

[0003] The field of invention is a method and means for scaling and orienting in photogrammetric engineering. Especially, the method and means concern a 3-dimensional object, such as a scaling cube, and method to scan a drift to achieve better accuracy in scanning and analysis.

[0004] Background

[0005] Rock mass characterization is crucial in the design of infrastructures such as tunnels and slopes. Rock mass, as the host material for these infrastructures, is inhomogeneous, consisting of both discontinuities and intact rock. Discontinuities play a vital role in the hydromechanical properties of rock mass. They can be characterized by various factors including the number of joint sets, distribution, type, persistence, orientation, spacing, filling, aperture, roughness, block size, wall rock, and shear strength. It can be concluded that the stability of a rock mass depends mainly on these discontinuities, which must be analyzed accurately. Therefore, the analysis and inspection of discontinuities often need to be carried out before, during, and after excavation. Several methods exist for analyzing discontinuities, such as remote sensing, the use of physical instruments, visual inspection, among others.

[0006] Among these methods, remote sensing techniques like laser scanning or Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry are popular. Each method has its advantages and disadvantages. For instance, laser scanning is a highly efficient and precise technique that has gained greater popularity compared to photogrammetry. However, it is also associated with higher costs. Photogrammetry, on the other hand, is a more cost- effective technique but is sensitive to various data acquisition factors such as illumination, camera quality, operator expertise, and the number of photographs taken, all of which can influence the final results. Unlike laser scanning, photogrammetry models typically require post-processing for scaling and orientation.

[0007] With the advancement of smartphone cameras, photogrammetry has become more accessible, requiring only a few simple steps, without expensive cameras or laser scanning equipment. The process can be further simplified by using videogrammetry, which, depending on the site, can provide appropriate and reasonable data in a shorter time frame compared to static photography.

[0008] An example of the prior art has been disclosed in German patent document DE 10201833562 B4. The document discloses a photogrammetric method for creating a model of and object. The method utilizes deployable marker cubes with one automatically detectable marker on each face and uses the cube-to- cube distances.

[0009] However, to work properly, the marker cubes disclosed must have several automatically detectable markers on each face, the method uses marker to marker distances within each face and it relies on predetermined marker-to- marker distances within each face.

[0010] Thus, the disclosed method is rigid, and not modifiable.

[0011] Summary of the invention

[0012] Aim is to provide a flexible and freely modifiable method and means for photogrammetry.

[0013] The invention is defined by the features of the independent claims. Some embodiments are defined in the dependent claims.

[0014] According to a first aspect, there is provided a 3D object for a 3D measurement. The 3D object comprises 1 D markers and at least one 2D scale bar comprising a predefined distance between at least two 1 D markers, at least three planes, of which at least one comprises 2D scale bar and the at least two comprise at least two 1 D markers both, wherein the at least three planes are non-parallel with each other, and the 3D object comprises an equipment configured to determine orientation of the 3D object.

[0015] The equipment may be embedded in the 3D object. The equipment may be a Global Navigation Satellite System, GNSS, a Global Positioning System, GPS, a compass, a rotation sensor, a gyroscope, or an acceleration sensor, for example.

[0016] A size of the 3D object may be known. The at least three planes may have the same distance to the center of the 3D object. The markers may comprise unique markers. At least one of the three planes may comprise a curved plane. The three planes may be orthogonal with each other.

[0017] The 2D scale bar(s) and / or 1 D markers may be automatically detectable. At least one of the predefined distances may be automatically detectable. At least one of the predefined distances may be measurable by photogrammetry or close-range photogrammetry.

[0018] The 3D object may be, or comprise, one of the following: a cube, a spherical object, a spheroid, a hexagon, a prism, a multifaceted object and a 3D shape having known cross-distances. The 3D object may comprise at least three nonparallel planes including at least three scale bars in each plane at predefined distances from each other. The 3D object may be a cube comprising the scale bar in at least one plane of the cube and at least two 1 D markers on each of the other planes of the cube. The 3D object may be a cube comprising the 1 D markers in each plane of the cube and at least one marker in the center of the cube.

[0019] The equipment configured to determine orientation of the 3D object may be embedded in the 3D object. The 3D object may comprise at least one of the following: a Global Navigation Satellite System, GNSS, a compass, one or more rotation sensors, a gyroscope, an accelerometer or a Global Positioning System, GPS. The 3D object may comprise a thermometer. The 3D object may be a 3D object for photogrammetry. The 3D object may comprise a multifaceted object, optionally a cube, having planar faces, with each pair of opposite faces is parallel to each other within a maximum annular deviation of 0,5 degrees. The 3D object may comprise a multifaceted object including at least three planes and at least two markers in each of the at least three planes, wherein the at least two markers are arranged such that in-plane shearing will not preserve the distances between the markers. The at least three planes of the 3D object may correspond to an equilateral triangle.

[0020] According to a second aspect, there is provided a method for 3D measuring comprising placing at least one 3D object according to the first aspect, capturing at least three photos of different field of view of the at least one 3D object, and saving the captured photos, the predefined distances and orientation of the 3D object.

[0021] The method may comprise measuring the predefined distances by photogrammetry or close-range photogrammetry. The method may comprise determining orientation of the 3D object by an embedded equipment of the 3D object. The method may comprise determining orientation using at least one of the following: a GNSS, a compass, a rotation sensor, a gyroscope, a GPS, and an accelerometer, which may optionally be embedded in the 3D object. The method may comprise inputting the predefined distances and orientation of the 3D object to a photogrammetry program.

[0022] According to a third aspect, there is provided use of the 3D object of the first aspect for photogrammetry.

[0023] According to a fourth aspect, there is provided use of the 3D object of the first aspect for construction yards, open pits and / or mines.

[0024] According to a fifth aspect, there is provided use of the 3D object of the first aspect in underground or tunnels. According to a sixth aspect, there is provided use of the 3D object of the first aspect for creating a 3D model.

[0025] List of figures

[0026] Figure 1 . presents nine points for mounting markers, scale bars and cubes.

[0027] Figure 2. presents different markers’ patterns for scaling photogrammetric 3D models, (a) individual marker (1 D), (b) scale bar (2D), and (c) scale cube (3D).

[0028] Figure 3. presents the lens specifications for ultra-wide camera lens of a smartphone used for photogrammetry.

[0029] Figure 4. presents smartphone positions for data acquisition.

[0030] Figure 5. presents Ground Control Points (GCPs) and their coordinate data on the orientation cube for orienting 3D models.

[0031] Figure 6. presents the Photogrammetric 3D models reconstructed by a smartphone with different scaling methods, (a) individual markers (1 D), (b) scale bars (2D), and (c) scale cubes (3D).

[0032] Figures are presented as illustrative examples and embodiments may not be limited solely to the illustrated parts, but modifications may be made under the scope as defined in the claims. Figures that may not fully present the claimed invention aim to provide better understanding on the context and relating technical field.

[0033] Detailed Description

[0034] There is provided a 3D object for 3D measurement, such as photogrammetry. The 3D object is especially usable for large-scale reconstructions. The 3D object comprises 1 D markers, which may be unique markers enabling identification of the 1 D markers. A 2D scale bar comprises a predefined distance between at least two 1 D markers. The 3D object comprises at least three planes of which at least one one comprises at least one 2D scale bar. At two of the at least three planes comprises at least two 1 D markers. The at least three planes are non-parallel with each other. The 3D object further comprises an equipment for determining orientation of the 3D object.

[0035] 3D objects may be used with photogrammetry for reconstructing or modeling rocks, tunnels, undergrounds, historical art, studies, construction yards, and so on. Photogrammetry enables modeling a real entity or environment. In this application photogrammetry is accompanied with a 3D object, which enables providing information on scale and orientation of a target or targeted environment.

[0036] Individual, unique markers are utilized for 1 D modelling. An individual marker is illustrated in Figure 2a. For 2D modeling a scale bar including a distance between two markers is used. A scale bar is illustrated in Figure 2b. For 3D modeling 3D objects, like cubes, are utilized. A 3D scale cube is illustrated in Figure 2c.

[0037] In the following a cube, which may be called a scale cube, is described. The (scale) cube is an example of a 3D object. The application or embodiments are not limited to the cube, but the described cube may be replaced by any 3D object according to this application. 3D object may be a 3D shape with curved surfaces, a cube, a spherical object, a spheroid, a hexagon, a prism, a multifaceted object and / or any 3D shape having known cross-distances, for example.

[0038] An embodiment of the invention is that it is multifaceted object with at least three independent planes, with at least 3 markers in each plane at predefined distances in an arrangement that in-plane shearing action will not keep the distances constant, for example (but not limited to) equilateral triangle.

[0039] A further embodiment of the invention is that it contains automatically detectable unique markers. A further embodiment of the invention is that it is a system having 2 or more predefined distances.

[0040] A further embodiment of the invention is that it has one or several of the distances which are automatically detectable.

[0041] A further embodiment of the invention is that predefined distances are measured using close-range photogrammetry of the markers with an object with known size, for example (but not limited to) a ceramic calibration piece. The relative distances of the unique markers are then recorded and saved to a machine-readable format such as (but not limited to) a comma separated value file.

[0042] Predefined distances relate to distances between markers in view of a known (reference) distance. Relative distances are mutual distances of the markers in relation to each other in a digital model.

[0043] A further embodiment of the invention is that the object is a cube with opposite edges in parallel with a maximum deviation of dip and / or each 0.5 degrees.

[0044] Dip surface corresponds to a plane. Dip direction may be 0-360 degrees and it corresponds to a direction to which water falls from the dip surface. Horizontal level is a dip angle of zero degrees. The dip angle may be between 0-90 degrees, wherein the 90 degrees faces downwards from the horizontal zero level.

[0045] A further embodiment of the invention is that each plane of the cube has markers in a square arrangement and one marker in the center of the square.

[0046] A further embodiment of the invention is that the cube has embedded GNSS location tracking and recording.

[0047] A further embodiment of the invention is that the cube has an embedded compass. A further embodiment of the invention is that the cube has one or more rotation sensors.

[0048] A further embodiment of the invention is that the cube has an internal temperature meter.

[0049] As mentioned earlier, the photogrammetry models obtained are neither scaled nor oriented. Different methods can be used to scale and orient a photogrammetry model, such as using known distances between specific points or referencing the known coordinates of points. The distance between known points is called a scale bar, which can be an approximate or accurate distance between two points within the model. These distances are typically measured using methods such as meter tape, Global Positioning System (GPS), or laser, though this process can be time-consuming. Predefined scale bars or orientation boards with certain markers and predefined distances can be used for photogrammetry to help reduce photography time. These scale bars can be easily distributed at the photogrammetry site, eliminating the need to measure distances between markers and speeding up the process.

[0050] Scaling 3D models using these methods cannot guarantee proper scaling in all three dimensions (X, Y, Z) because the distributions of scale bars are not clearly defined. However, using a predefined 3D scale bar, which can scale and orient a photogrammetry model with known distances and proper distribution in all directions, can help to overcome this problem. For this purpose, a cube with sides covered by predefined distances was used to scale a 3D model of a tunnel drift obtained by smartphone (iPhone 15 Pro Max) photogrammetry and compared with individual markers (1 D), scale bars (2D) and scale cubes (3D). The accuracy of the models was assessed by comparing the calculated distances with the actual distances.

[0051] Site of data collection

[0052] A tunnel drift was selected as a site for data collection. The drift dimensions are 2.5 m in height, 4.5 m in width, and 3 m in length. The drift is hosted by a magmatic granite rock mass (Figure 1 ). Nine points for mounting markers, scale bars and cubes are shown in Figure 1 .

[0053] Scaling methods

[0054] Three different scaling methods were selected to scale and analyze the photogrammetric data. In the first method, nine individual markers (1 D) were mounted on the walls, and photography was conducted (Figure 2(a)). The distances between center to center of the markers were measured using a Leica DISTO S910 laser distance meter, which has a resolution of 1 mm, for pairs such as 1 to 2, 2 to 3, and so on, up to 8 to 9. These distances were used to scale the 3D model. In the second method, the individual markers were replaced with nine scale bars (2D). The distance between markers for each scale bar was 105 mm (Figure 2(b)). Finally, the scale bars were replaced with nine scale cubes (Figure 2(c)), with distances of 105 mm for vertical and horizontal measurements and 148.492 mm for diagonal distances. Photogrammetry was conducted separately for each scaling method. The distance between markers for the scale bars and scale cubes was measured by GIMP software with an accuracy of 1 pm. All markers were printed with the same printer at a resolution of 1200 dpi. The distance between the markers was verified using a high-precision coordinate table with a 1 pm resolution.

[0055] Distances between markers for the scale bars, and / or between (scale) cubes may be measured using photogrammetry or close-range photogrammetry.

[0056] Smartphone specifications

[0057] In this study, the ultra-wide camera lens of an iPhone 15 Pro Max smartphone was used for photogrammetry. The lens specifications are shown in Figure 3. The use of a smartphone enables quick and easy photography for engineering applications, such as rock mass mapping. Shutter speed and ISO were adjusted based on the prevailing site conditions to optimize image quality. The automatic lens correction was on in the smartphone. The used camera of iPhone 15 Pro Max smartphone comprises an ultra-wide camera lens of 12 MPix, focal length of 2 mm, 35 mm equivalent focal length of 13 mm, pixel size of 1.4 pm, aperture of f / 2.2, image resolution in pixels of 4032 x 3024, actual sensor size of 5.6 mm x 4.2 mm, and format of JPEG.

[0058] Any smartphone camera or any camera suitable for the purpose may be utilized. Number of cameras may be utilized. Instead of moving a camera or utilizing multiple cameras, structured light photogrammetry may be utilized. In structured light photogrammetry camera stays in its place and a projected light is arranged to form stripes to be photographed at different locations of the view.

[0059] Site preparation and photogrammetric data collection

[0060] To have sufficient illumination for photography, the drift was illuminated by battery-powered DeWALT DCL074-XJ LED lights providing 5000 lux with 360° coverage (Figure 4). One cube served as an orientation cube to align the 3D models toward the north. It was aligned with a compass to ensure it accurately pointed north and was placed in the middle of the drift (Figure 4).

[0061] After mounting each marker’s pattern, photography was conducted according to Figure 4. Nine positions were selected and five photos were taken from each spot: one at 0°, and the others at ± 30° angles in the upward, downward, left, and right directions. In total, 135 photos were taken for each scaling method.

[0062] Number of photos is not limited. Increased number of photos may increase accuracy and / or reduce deviation from real-world measurements. Also number of cubes may be increased. At least three photos of different field of view shall be taken of the (at least one) cube to enable utilization of the photos for photogrammetry.

[0063] Photogrammetric data processing

[0064] RealityCapture 1 .4 was used to reconstruct 3D models of the drift with various scaling methods. After importing the photos, the markers were detected using the marker detection tool in the software. To ensure an accurate 3D model, the images were first grouped for calibration in RealityCapture. The Brown 4 with Tangential 2 distortion model was then applied to correct photo distortion through self-calibration, with each photo adjusted based on this model. After aligning the 3D models, the distances between markers were defined and updated in the software. For further accuracy, any calculated distances that deviated by more than two standard deviations from the actual values were eliminated to prevent significant errors in the final model. After this elimination, the model was realigned again. The calculated distances were exported to assess accuracy. The model was then reconstructed with normal details, textured, and exported as a 3D point cloud. To orient the 3D models, the orientation cube and three points on its top surface (Figure 5) served as ground control points (GCPs). The orientation cube was not used for scaling.

[0065] Figure 5 illustrates ground control points and their coordinate data on an orientation cube for three markers, being GCP1 (0, 0, 0), GCP2 (0.105, 0,0), and GCP3 (0, 0.105, 0).

[0066] Any photogrammetry program, algorithm, or software may be used. A 3D object, like cube, may include markers, which are automatically detectable. The markers may be localized in photos. Distance between the markers may be known, detected and / or measured. Distances enable to provide a scale.

[0067] The cube includes an equipment for providing orientation. The equipment may be included or embedded to the (scale) cube, for example at a center of the cube. Equipment may comprise GNSS or GPS. Those may utilize wireless network connection, for example a multiantenna Wireless Fidelity (Wi-Fi). For possible underground measurements, or for other places being out of network coverage, a barometer, a gyroscope, a compass, an accelerometer, a rotation sensor or alike orientation means may be used.

[0068] Accuracy assessment

[0069] To verify the accuracy of the 3D models using different scaling methods, the distances between markers calculated in RealityCapture were compared to the actual measurements. The root mean square error (RMSE) was then calculated to assess alignment accuracy (Equation 1 ). where i represents the index of each individual distance, and n denotes the total number of distances used to check the model.

[0070] Results

[0071] Photogrammetric 3D models

[0072] Figure 6 shows the 3D photogrammetric models reconstructed using different scaling methods. Each model contains approximately 30 million points. The total alignment times varied depending on the scaling method, with individual markers taking 59 seconds, scale bars taking 35 seconds, and scale cubes taking 31 seconds. Using more markers improves alignment speed, which is particularly beneficial for large-scale modeling, where scanning extensive areas can be time-consuming. Additionally, the ultra-wide camera of the iPhone 15 Pro Max demonstrated its capability for photogrammetry in capturing high-detail 3D models.

[0073] Accuracy assessment

[0074] A comparison between the actual distances and the photogrammetrically calculated distances demonstrates that accuracy improves with an increased number of markers and the transition from 1 D to 3D markers. The RMSE for individual markers (1 D) was 0.627 mm, while the RMSE for scale bars (2D) exhibited significant improvement, reducing to 0.382 mm. Further-more, the RMSE for scale cubes (3D) demonstrated an additional decrease to 0.238 mm. This progression in accuracy highlights the effectiveness of using 3D scale cubes for achieving highly accurate 3D models. The increased precision from the 3D scale cubes offers several benefits. First, it ensures that the 3D models are correctly scaled, allowing for the detection of small changes and movements. This could be important for monitoring and risk assessment in rock masses, where even small changes and movements can significantly impact stability and safety. Additionally, using 3D cubes could reduce errors in spatial dimensions and provide a higher level of confidence in 3D models' reliability.

[0075] To assess the accuracy of 3D models, three scaling methods were compared: 1 D individual markers, 2D scale bars, and 3D (scale) cubes. The results showed that 3D cubes produced the highest accurate models, with minimal deviations from real-world measurements, as confirmed by RMSE (Root Mean Square Error) evaluations. In addition to improving accuracy, 3D cubes reduced alignment time, making the process more efficient for large-scale modeling where both speed and precision are crucial.

[0076] The comparison highlights the importance of selecting the appropriate scaling method based on model complexity and size. The 1 D method was less accurate. The 2D scale bar method improved precision, but the 3D cube method was the most effective, reducing errors in large-scale reconstructions.

[0077] These findings demonstrate that choosing the right scaling method is essential for the accuracy of photogrammetric 3D models. Transitioning from 1 D markers to 3D cubes enhances measurement precision and alignment efficiency.

[0078] This invention also evaluated the use of smartphones, specifically the iPhone 15 Pro Max, for 3D model reconstruction in rock masses. The results suggest that smartphones, combined with proper scaling techniques, can serve as a cost-effective alternative to traditional equipment for capturing high-resolution models. This has practical applications in fields like rock mass assessments, tunnel inspections, and underground engineering. It is to be understood that aspects, examples and embodiments disclosed are not limited to the particular structures, process steps, or materials disclosed herein, but are extended to equivalents thereof as would be recognized by those ordinarily skilled in the relevant arts. It should also be understood that terminology employed herein is used for the purpose of describing particular embodiments only and is not intended to be limiting.

[0079] The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the previous description, numerous specific details are provided, such as examples of structures, lengths, widths, shapes, etc., to provide a thorough understanding of embodiments. One skilled in the relevant art will recognize, however, that embodiments can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well- known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the invention.

[0080] While the forgoing examples are illustrative of the principles of the present invention in one or more particular applications, it will be apparent to those of ordinary skill in the art that numerous modifications in form, usage and details of implementation can be made without the exercise of inventive faculty, and without departing from the principles and concepts of the invention. Accordingly, it is not intended that the invention be limited, except as by the claims set forth below.

[0081] The verbs “to comprise” and “to include” are used in this document as open limitations that neither exclude nor require the existence of also un-recited features. The features recited in depending claims are mutually freely combinable unless otherwise explicitly stated. Furthermore, it is to be understood that the use of “a” or “an”, i.e. a singular form, throughout this application does not exclude a plurality.

Claims

CLAIMS1 . A three-dimensional, 3D, object for a 3D measurement, the 3D object comprising- one-dimensional, 1 D, markers and at least one two-dimensional, 2D, scale bar, comprising a predefined distance between at least two 1 D markers,- at least three planes of which at least one comprising the 2D scale bar and at least two comprising at least two 1 D markers, wherein the at least three planes are non-parallel with each other, and- an equipment configured to determine orientation of the 3D object.

2. The 3D object according to the claim 1 , wherein a size of the 3D object is known.

3. The 3D object according to any one of the previous claims, wherein the at least three planes have the same distance to the center of the 3D object.

4. The 3D object according to the claim 1 or 2, wherein the 3D object comprises at least three planes, which are orthogonal with each other.

5. The 3D object according to any one of the previous claims, wherein the 1 D markers comprise unique 1 D markers.

6. The 3D object according to any one of the previous claims, wherein at least one of the at least three planes comprises a curved plane.

7. The 3D object according to any one of the previous claims, wherein the 1 D markers and / or the 2D scale bars are automatically detectable.

8. The 3D object according to any one of the previous claims, wherein the predefined distance is automatically detectable.

9. The 3D object according to any one of the previous claims, wherein the predefined distance is measurable by photogrammetry or close-range photogrammetry.

10. The 3D object according to any one of the previous claims, wherein the 3D object comprises one of the following: a cube, a spherical object, a spheroid, a hexagon, a prism, a multifaceted object and a 3D shape having known cross-distances.11 .The 3D object according to any one of the previous claims, wherein the 3D object comprises at least three non-parallel planes including at least three 2D scale bars or 1 D markers in each plane at predefined distances from each other.

12. The 3D object according to any one of the previous claims, wherein the 3D object is a cube having planar faces such that each pair of opposite faces is arranged parallel to each other within a maximum angular deviation of 0.5 degrees13. The 3D object according to any one of the previous claims, wherein the 3D object is a cube comprising the 1 D markers in each plane of the cube and at least one 1 D marker in the center of the cube.

14. The 3D object according to any one of the previous claims, wherein the equipment configured to determine orientation of the 3D object is embedded in the 3D object.

15. The 3D object according to the any one of the previous claims wherein the equipment comprises a Global Navigation Satellite System.

16. The 3D object according to any one of the previous claims, wherein the equipment comprises a compass.

17. The 3D object according to any one of the previous claims, wherein the equipment comprises one or more rotation sensors.

18. The 3D object according to any one of the previous claims, wherein the equipment cube comprises a gyroscope.

19. The 3D object according to any one of the previous claims, wherein the equipment cube comprises an accelerometer.

20. The 3D object according to any one of the previous claims, wherein the equipment comprises a Global Positioning System.21 . The 3D object according to any one of the previous claims, wherein the 3D object comprises a thermometer.

22. The 3D object according to any one of the previous claims, comprising the 3D object for a 3D photogrammetry.

23. The 3D object according to any one of the previous claims, wherein the 3D object comprises a multifaceted object including at least three planes and at least two markers in each of the at least three planes arranged such that in-plane shearing action fails to preserve the distances between the markers.

24. The 3D object according to any one of the previous claims, wherein the at least three planes of the 3D object correspond to an equilateral triangle.

25. Method for 3D measuring comprising- placing at least one 3D object according to any one of the claims 1 -24,- capturing at least three photos of different field of view of the at least one 3D object, and- saving the captured photos, the predefined distances and orientation of the 3D object.

26. A method according to the claim 24, comprising measuring the predefined distances by photogrammetry or close-range photogrammetry.

27. A method according to any one of the claims 24-26, comprising determining orientation of the 3D object by an embedded equipment of the 3D object.

28. A method according to the claim 27, wherein the orientation is determined by at least one of the following: a Global Navigation Satellite System, a compass, a rotation sensor, a gyroscope and a Global Positioning System included in the 3D object.

29. A method according to any one of the claims 25-28, comprising inputting the predefined distances and orientation of the 3D object to a photogrammetry program.

30. Use of the 3D object according to the claims 1 -24 for photogrammetry.31 . Use of the 3D object according to the claims 1 -24 for construction yards, open pits and / or mines.

32. Use of the 3D object according to the claims 1 -24 in underground or tunnels.

33. Use of the 3D object according to the claims 1 -24 for creating a 3D model.

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