3-D VISUAL RECONSTRUCTION : ASYSTEM PERSPECTIVE
Student:
Guillermo Enrique Medina Zegarra
Advisor:PhD. Edgar Lobaton, USA
Co-AdvisorPhD. Nestor Calvo, Argentina
Arequipa, Peru
May 07, 2012
1
Index
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
2
Index
1 IntroductionMotivation and contextDefinition the problemGeneral objectiveSpecific objectives
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
3
Motivation and context
Limitations on pre-Renaissance to create 3D.
The artists during the Renaissance and the depth.
The vanishing points and three dimensions.
(a) Jesus intoJerusalem
(b) The School of Athens
Figura: Painting pre-Renaissance and Renaissance [Ma et al., 2004].
3
Motivation and context
Limitations on pre-Renaissance to create 3D.
The artists during the Renaissance and the depth.
The vanishing points and three dimensions.
(a) Jesus intoJerusalem
(b) The School of Athens
Figura: Painting pre-Renaissance and Renaissance [Ma et al., 2004].
3
Motivation and context
Limitations on pre-Renaissance to create 3D.
The artists during the Renaissance and the depth.
The vanishing points and three dimensions.
(a) Jesus intoJerusalem
(b) The School of Athens
Figura: Painting pre-Renaissance and Renaissance [Ma et al., 2004].
4
Definition the problem
Physical architecture, location, distribution and lighting.
(a) One camara[Cipolla et al., 2010]
(b) Artificial lighting[VISGRAF., 2012]
5
Definition the problem (cont...)
Figura: How to get the parameters to map an object to the image plane? [Faugeras, 1993].
6
Definition the problem (cont...)
Figura: How to find corresponding points ? [Szeliski, 2011].
7
Definition the problem (cont...)
Figura: How to find a 3D point of each pair of corresponding points ?[Szeliski, 2011].
8
Definition the problem (cont...)
Figura: How to reconstruction and smooth a surface from a cloud ofpoints ? [Hartley and Zisserman, 2004].
9
General objective
Objetivo general
Propose a model for the reconstruction of a 3D image of an objectfrom two images captured by two cameras located adequately.
10
Specific objectives
Specific objectives
Position two digital cameras on a physical architecture for imageacquisition and calibration.
Rectification of the stereo image pair and calculate the disparitymap through the normalized cross-correlation.
Create the object’s surface from the Delaunay triangulation of thedisparity map.
11
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
12
Pinhole camera model
Help to understand the image formation from geometric point ofview.
Parts of the pinhole camera model: optical center (o), focaldistance (f ) and image plane (I ).
x = op ∩ I x ∈ R2 , p ∈ R3
Figura: Pinhole camera model [Ma et al., 2004].
13
Pinhole camera model (cont...)
Figura: Example of the projection of an object on image plane .
14
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
15
Epipolar geometry
Study the geometric relationship and mathematical analysis of a3-D p point in their image planes.
Figura: Two projections x1, x2 ∈ R2 of a 3-D point p from two vantagepoints [Ma et al., 2004].
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Epipolar geometry (cont...)
Figura: Example of the projection of a cube image on two image planes.
17
Rectification
Figura: Rectification of the stereo image pair [Fusiello et al., 2000].
18
Disparity calculation
(a) (b) Disparity map
(a - b) Tsukuba image pair [Scharstein and Szeliski, 2002].
19
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
20
Pipeline of the proposal
21
Description of the proposed pipeline
Physical architecture
Image acquisition
Calibration
Canon SD1200 Sony DSC-S750
21
Description of the proposed pipeline
Physical architecture
Image acquisition
Calibration
features Sony DSC-S750 Canon SD1200 ISSensor type CCD CCDImage size 640 × 480 640 × 480ISO 100 100Flash off off
Technical characteristics of the two digital cameras
21
Description of the proposed pipeline
Physical architecture
Image acquisition
Calibration
Chessboard (7 × 10)
22
Description of the proposed pipeline
Rectification
Linear search
The correspondence of points isin the same horizontal line
Original images Rectified images
23
Description of the proposed pipeline
Pre-processing
Manual segmentation
Gaussian filter
Rectified images Pre-processed images
24
Description of the proposed pipeline
Disparity map
Normalized Cross-Correlation
Median filter
Left image pre-processed Right image pre-processed Disparity map
25
Description of the proposed pipeline
3-D mesh
Delaunay triangulation
Intersection of lines
3-D mesh
Disparity map Point Cloud 3-D mesh
26
Description of the proposed pipeline
Reconstructed model
Smoothing the surface
Texturing of the right image
Creation of the surface Smoothing of the surface Texturing of the model
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“Cubo magico”
Original images Rectified images Pre-processed images
28
“Cubo magico” (cont...)
Disparity map Point Cloud 3-D mesh
Creation of the surface Smoothing of the surface Texturing of the model
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
29
Multiple views of the “Magic Cube”
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Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 ResultsTeddy bearHuman face
6 Limitations and problems founded
7 Conclusions and future work
31
Teddy bear
Original images Rectified imagenes Pre-processed imagenes
32
Teddy bear (cont...)
Disparity map Cloud of points 3-D mesh
Creation of the surface Smoothing of the surface Texturing of the model
33
Human face
Original images Rectified imagenes Pre-processed imagenes
34
Human face (cont...)
Cloud of points Model without smoothing Smoothing model “Transformed” model
3-D mesh Model without smoothing Smoothing model “Transformed” model
35
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
36
Limitations and problems founded
neighbourhood size Imperfections of the created model
37
Limitations and problems founded (cont...)
Imperfect original image Imperfect original image
Wrong disparity map “Amorphous” 3-D reconstruction
38
Index
1 Introduction
2 Image formation
3 Geometry from two views
4 Proposal
5 Results
6 Limitations and problems founded
7 Conclusions and future work
39
Conclusions
Physic architecture was designed simple and profit.
Lighting conditions must be adequate.
A pipeline was proposed with a sequence of steps needed to get a3-D reconstruction of a stereo image pair.
The method for the disparity calculation is simple and no robust.
There is a strong dependency between each step of thereconstruction.
40
Future work
Create an environment withappropriate conditions for calibration,lighting and image acquisition.
Physical architecture and artificial lighting [Bradley et al., 2008]
Use multiple cameras.
Multiple views [Hartley and Zisserman, 2004]
40
Future work
Create an environment withappropriate conditions for calibration,lighting and image acquisition.
Physical architecture and artificial lighting [Bradley et al., 2008]
Use multiple cameras.
Multiple views [Hartley and Zisserman, 2004]
41
Future work (cont...)
Use robust methods.
42
Publicated on
Symposium article“3-D visual reconstruction : a system perspective.”G. Medina-Zegarra y E. Lobaton2nd International Symposium on Innovation andTechnology (2011)pag. 102-107, November 28-30, Lima, PeruISBN: 978-612-45917-1-6Place: Technological University of Peru
Editor: International Institute of Innovation andTechnology (IIITEC)Chair: Mario Chauca Saavedra
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Acknowledgements
X PhD. Alex CuadrosX PhD. Alfedro MirandaX Mag. Alfedro PazX PhD. Carlos LeytonX PhD(c). Christian Lopez del AlamoX PhD. Eduardo TejadaX PhD. Jesus MenaX PhD. Jose Corrales-NievesX PhD(c). Juan Carlos GutierrezX Lic. Luıs ParejaX Family Barrios Neyra
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References
Bradley, D., Popa, T., Sheffer, A., Heidrich, W., and Boubekeur, T. (2008).
Markerless garment capture.ACM Transactions on Graphics (TOG), 27:99:1–99:9.
Cipolla, R., Battiato, S., and Farinella, G. M. (2010).
Computer Vision: Detection, Recognition and Reconstruction.Springer.
Faugeras, O. (1993).
Three-dimensional Computer Vision: A Geometric Viewpoint.The MIT Press. ISBN: 0262061589.
Fusiello, A., Trucco, E., and Verri, A. (2000).
A compact algorithm for rectification of stereo pairs.Machine Vision and Applications, 12:16–22.
Hartley, R. and Zisserman, A. (2004).
Multiple View Geometry in Computer Vision. Second Edition.Cambridge University Press. ISBN: 0521540518.
Ma, Y., Soatto, S., Kosecka, J., and Sastry, S. S. (2004).
An Invitation to 3D Vision from Images to Geometric Models.Springer. ISBN: 0387008934.
Scharstein, D. and Szeliski, R. (2002).
A taxonomy and evaluation of dense two-frame stereo correspondence algorithms.International Journal of Computer Vision, 47:7–42.
Szeliski, R. (2011).
Computer Vision: Algorithms and Applications.Springer. ISBN: 9781848829343.
VISGRAF. (2012).
Vision and graphics laboratory.Institute of Pure and Applied Mathematics (IMPA) http: // w3. impa. br/ ~ anafucs/ 3d_ museum/ 14Enero.
3-D VISUAL RECONSTRUCTION : ASYSTEM PERSPECTIVE
Student:
Guillermo Enrique Medina Zegarra
Advisor:PhD. Edgar Lobaton, USA
Co-AdvisorPhD. Nestor Calvo, Argentina
Arequipa, Peru
May 07, 2012
44
45
View points (perception)
(a) The glass is half fullor half empty ?
(b) is it a duck or a rabbit ?
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