Accuracy Analysis of Three-Dimensional Model Reconstructed by Spherical Video Images

1. ACCURACY ANALYSIS OF THREE-DIMENSIONAL MODEL
RECONSTRUCTED BY SPHERICAL VIDEO IMAGES
Muhammad Irsyadi Firdaus1 & Jiann-Yeou Rau2
1Master Student and 2Professor
Department of Geomatics
National Cheng Kung University, Taiwan (R.O.C)
A Presentation at
International Symposium on Remote Sensing (ISRS 2018)
Alpensia Convention Center, Pyeongchang, Korea
May 9 – 11, 2018

2. 1
2
3
Motivation
Methodology
Results
Conclusion
Outline
Background
Problem
Study Area
Equipment
Data and Workflow
Aerial Triangulation
Dense Point Cloud
Evaluation of the image geo-referencing
Accuracy assessment of a point cloud
Objective
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3. Motivation
01
Background
02
Problem
03
Objective
Spherical image of an indoor
Stitching Spherical imagery is created by
digitally stitching multiple images
taken from the same position with
different orientations.
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3

4. Motivation
01
Background
02
Problem
03
Objective
Frame-based camera
1. Smaller FOV
2. Slower data acquisition
3. High costs
1. Time
2. Human resource
Purpose : to reconstruct 3D
indoor/outdoor environment
Spherical camera
1. 720 degrees FOV
2. Rapid data acquisition
3. Low costs
1. Time
2. Human resourceSpecific Object
Indoor environment
outdoor environment
4

5. Motivation
01
Background
02
Problem
03
Objective
• To evaluate the
performance of 3D model
reconstruction pipeline by
using a spherical video
camera.
• Compare with TLS data and
several reference points.
reference points
5

6. Methodology
01
Study Area
02
Equipment
03
Data and Workflow
• Located at the Geomatics Building,
NCKU, Taiwan.
• The total number of spherical
images acquired is 134.
6

7. Methodology
01
Study Area
02
Equipment
03
Data and Workflow
Software
Table 1.Garmin VIRB 360
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8. Methodology
01
Study Area
02
Equipment
03
Data and Workflow
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9. Methodology
01
Study Area
02
Equipment
03
Data and Workflow
Data Acquisition
Acquire
Spherical Video
Extract images from video
Marking reference point (control/
check) & Aerial Triangulation &
camera self-calibration
Aerial Triangulation
accuracy analysis
Dense Image Matching
Acquire
TLS Data
Registration
Point Cloud
Comparisons
TLS Point Cloud
Point cloud
Collect reference points
Using Total Station
Figure 2. Spherical video images
Figure 3. TLS point cloud
9

10. Results
01
Aerial Triangulation & Dense Point Cloud
02
Evaluation of the image geo-referencing
03
Accuracy assessment of a point cloud
Figure 4. Sparse point
cloud with camera location
Figure 5. Dense point cloud Figure 6. The 3D texture
model is very noisy
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11. GlassHomogeneous Surface
Glass
• Glass refraction
• Unbalance
illumination
Glass
Stitching Images Why does the model have a lot of noise?
Results
01
Aerial Triangulation & Dense Point Cloud
02
Evaluation of the image geo-referencing
03
Accuracy assessment of a point cloud
11

12. Results
01
Aerial Triangulation & Dense Point Cloud
02
Evaluation of the image geo-referencing
03
Accuracy assessment of a point cloud
Reference point well distributed at the full frame of the image
horizontal errors vertical errors reprojection errors
No. of GCPs = 6 4.274 4.520 8.536
No. of Check Points = 23 12.070 11.604 31.489
Reference point located in the middle portion of the image
horizontal errors vertical errors reprojection errors
No. of GCPs = 7 3.031 3.824 6.606
No. of Check Points = 15 6.822 6.742 21.436
Table 2. The statistics for control points and check-points with the spherical
projections generated with different distribution of reference point. (unit: cm)
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13. Results
01
Aerial Triangulation & Dense Point Cloud
02
Evaluation of the image geo-referencing
03
Accuracy assessment of a point cloud
Max Discrepancy 25.71
Average Distance 3.47
Max Error 0.76
RMS 0.46
Standard Deviation 3.76
Type Number
Dense Point Cloud 4,063,465
TLS Point Cloud 56,281,574
Table 3. The matching results
Table 4. Statistics of distance computation (unit: cm)
Figure 9. The distance between photogrammetric
point cloud and TLS point cloud
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14. Indoor and Outdoor Environment
Results
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15. Conclusion
The geometric detail and
accuracy of point clouds
generated is too low
The generated 3D model still can
be applied to many applications
2
3
4
5
1
The reference point located in the middle of
the portion of the image has better accuracy
The major problem that
causes such a large error
is the stitching algorithm
Several factors affect the accuracy and
details
1. spherical camera calibration
2. spherical image stitching algorithm
3. image resolution
4. object material and the variability of
illumination conditions in the rooms.
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16. Thank You for Your Attention
Say, "Are those who know equal to those who do not know?
[Az-Zumar, 39:9]