THE 3D MODELLING USING FRAME CAMERAS AND PANORAMIC CAMERA

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Muhammad Irsyadi FirdausAdvisor: Jian-Yeou RauLaboratory of Cyber City

OutlineIntroduction

Method

Result

Conclusion

Future work

Reference

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Introduction (I)

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The frame camera is used by users of digital single-lens reflex cameras (DSLRs) as a shorthand for animage sensor format which is the same size as35mm format (36 mm × 24 mm) film.

Figure 1. kinds of the frame camera size

Introduction (II)

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Panoramic imagery is created either by digitallystitching together multiple images from thesame position (left/right, up/down) or byrotating a camera with conventional optics, andan area or line sensor.

Figure 2. circular images

Figure 3. Panoramic imagery

Geometry of Digital Frame Camera

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The geometry of image formation can be modeled as aperspective projection, which describes the relationshipbetween the camera lens system and the image plane.

Figure 5. Perspective projection

Figure 4. Geometry of Digital Frame Camera

Geometry of Panoramic Camera

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Panoramic photogrammetry is based on a cylindricalimaging model, as generated by numerous analogue anddigital panoramic cameras or by a computational fusionof individual central perspective images. Assuming thecamera rotation corresponds to a horizontal scan, theresulting panoramic image has central perspectiveimaging properties in the vertical direction only.

Figure 6. Coordinate systems defining a cylindrical panorama

Objective

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Building point clouds and textured meshes from both cameras in indoor. Furthermore, the same imaging

resources can be to accuracy evaluation.

Methodology

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Acquires a pair of fisheye images that are then stitchedinside (a) the mobile phone or with (b) the ActionDirection desktop application. In addition, the fisheyeimages were stitched with software for panoramicphotography (PTGui (c) and Autopano Giga (d)). (Fig. 6).

Figure 7. The different options for the generation of equirectangular projections

Required a preliminary calibration project for theestimation of distortion coefficients and relativeorientation between the fisheye image pair

Default solutions

Methodology

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Metric accuracy of single fisheye images

Relative orientation of front and rear-facing images

Images have the typical configuration forcamera calibration, i.e. several convergentimages with roll variations.

The calibration procedure aims at determining therelative position and attitude of front- and rear-facingimages, as well as their distortion parameters.

3D Modeling

3D modeling software

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The spherical camera model is also availablein some 3D modeling software from images

Results

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Table 1. Accuracy achieved with the front-facing camera Metric accuracy of single fisheye images

Such results confirm the good metric

quality of the Samsung Gear 360 when the

original fisheye images are used for

photogrammetric applications

The used software is ContextCapture,

which allows one to process fisheye images

with a mathematical formulation based on

the asymmetric camera model.

Results

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Relative orientation of front and rear-facing images

Fig. 8. The special calibration tool used to estimate the relative orientation between front and rear facing images. PTGui project with all images and the final result in which

only a pair of front and rear facing images are used for generating the equirectangular projection.

The RMS of pixel coordinates achievedwith PTGui was about ±8.5 pixels, that isnot an optimal result.

Results with AutoPano Giga were insteadbetter. The achieved RMS of imagecoordinates was ±3.3 pixels

Results

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Evaluation Of Metric Accuracy With Equirectangular Projections

Table 1. The statistics for control points and check points with the equirectangular projections

generated with different solutions.

Figure 9. One of the equirectangular projections

and the 8 targets used as control and check

points.

Results

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HDR 360o photo capturingSLR photo capturing

Coloured point cloud (11.989.171 points,medium quality settings) and texturedmesh were obtained by using 60 frameimages (18 Mpx). Photo capturing took 2.5hours.

Coloured point cloud (2.373.124 points,medium quality settings) and texturedmesh were obtained by using 12 sphericalimages (50 Mpx).

Camera position

Results

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Canon 550 D SLR point cloud HDR 3600 point cloud FARO Focus 3D X130

coloured point cloud

As it is shown in the results, the geometricdefinition is very good, very close to theone obtained by laser scanning.Nevertheless, some strong shadows can beseen on the vaults and near the floor.

Coloured point cloud (41.892.875 pointsafter registration and subsampling,medium quality settings) was obtained byusing 4 scan stations. Scan data capturingtook 50 min.

Comparisons of point cloud

Results

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Canon 550 D SRL textured mesh HDR 3600 textured mesh

Point cloud resolution obtained with HDR 3600 is clearlylower but enough for general geometry documentation.Furthermore, dense point cloud showed is obtained byusing “medium” PhotoScan settings and therefore, pointcloud with higher density could be obtained if selected“high” or “ultra-high” settings.

Comparisons of textured mesh

Results

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Table 2. Canon 550 D SRL frames compared

to NCTech iSTAR HDR spherical images

Comparison of frame camera methodology against the spherical methodology

Results

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At first sight, the point cloudobtained by using Canon 550 DSLR data seems more uniform.The majority of the points showeda distance difference of 0.002 m,being the most common valuesunder 0.025 m.

Canon 550 DSLR point cloud deviation compared to FARO Focus 3D X130

Results

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The results showed by HDR3600 data comparison seemless uniform at first sight.Nevertheless, the graphicdistribution of values is quitesimilar. The majority of thepoints showed distancedifferences of 0.002 m, beingmost common values under0.025 m.

HDR 3600 point cloud deviation compared to FARO Focus 3D X130

Results

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The reconstruction from front rear facing fisheye images has a

better accuracy but is partially incomplete, especially the area

above the camera.

The achieved mesh has a better quality than thatgenerated by equirectangular image

On the other hand, the reconstruction is partiallyincomplete, especially the area of the vault, which wasinstead modeled in the case of equirectangularprojections

Single equirectangular projections orpairs of front- and rear-facing images?

Conclusion1. HDR 360 accurate pre-calibrated cameras, image matching techniques also became

competitive in terms of color quality and time-consuming.

2. Point cloud resolution gained from image matching techniques is enough for both general and detail documentation.

3. Image matching techniques by using HDR 360 accurate pre-calibrated cameras make the task easier and faster

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Future Work1. Build a 3D model of a video model, where the video model can be extracted into an image

model.

2. In other cases, for 3D modeling we can consider light. The point is the comparison of the intensity of light from inside and outside the room.

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ReferencesA. Pérez Ramos and G. Robleda Prieto, 2016, Only Image Based For The 3D

Metric Survey Of Gothic Structures By Using Frame Cameras AndPanoramic Cameras, ISPRS, Volume XLI-B5.

L. Barazzetti, M. Previtali, and F. Roncoroni, 2017, 3D Modelling With TheSamsung Gear 360, ISPRS, Volume XLII-2/W3

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Thank you for your attention

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