Post on 05-Dec-2014
description
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
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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].
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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]
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Definition the problem (cont...)
Figura: How to get the parameters to map an object to the image plane? [Faugeras, 1993].
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Definition the problem (cont...)
Figura: How to find corresponding points ? [Szeliski, 2011].
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Definition the problem (cont...)
Figura: How to find a 3D point of each pair of corresponding points ?[Szeliski, 2011].
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Definition the problem (cont...)
Figura: How to reconstruction and smooth a surface from a cloud ofpoints ? [Hartley and Zisserman, 2004].
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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.
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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.
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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
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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].
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Pinhole camera model (cont...)
Figura: Example of the projection of an object on image plane .
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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
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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.
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Rectification
Figura: Rectification of the stereo image pair [Fusiello et al., 2000].
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Disparity calculation
(a) (b) Disparity map
(a - b) Tsukuba image pair [Scharstein and Szeliski, 2002].
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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
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Pipeline of the proposal
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Description of the proposed pipeline
Physical architecture
Image acquisition
Calibration
Canon SD1200 Sony DSC-S750
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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
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Description of the proposed pipeline
Physical architecture
Image acquisition
Calibration
Chessboard (7 × 10)
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Description of the proposed pipeline
Rectification
Linear search
The correspondence of points isin the same horizontal line
Original images Rectified images
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Description of the proposed pipeline
Pre-processing
Manual segmentation
Gaussian filter
Rectified images Pre-processed images
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Description of the proposed pipeline
Disparity map
Normalized Cross-Correlation
Median filter
Left image pre-processed Right image pre-processed Disparity map
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Description of the proposed pipeline
3-D mesh
Delaunay triangulation
Intersection of lines
3-D mesh
Disparity map Point Cloud 3-D mesh
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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
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“Cubo magico” (cont...)
Disparity map Point Cloud 3-D mesh
Creation of the surface Smoothing of the surface Texturing of the model
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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Multiple views of the “Magic Cube”
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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
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Teddy bear
Original images Rectified imagenes Pre-processed imagenes
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Teddy bear (cont...)
Disparity map Cloud of points 3-D mesh
Creation of the surface Smoothing of the surface Texturing of the model
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Human face
Original images Rectified imagenes Pre-processed imagenes
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Human face (cont...)
Cloud of points Model without smoothing Smoothing model “Transformed” model
3-D mesh Model without smoothing Smoothing model “Transformed” model
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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
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Limitations and problems founded
neighbourhood size Imperfections of the created model
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Limitations and problems founded (cont...)
Imperfect original image Imperfect original image
Wrong disparity map “Amorphous” 3-D reconstruction
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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
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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.
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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]
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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]
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Future work (cont...)
Use robust methods.
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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
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View points (perception)
(a) The glass is half fullor half empty ?
(b) is it a duck or a rabbit ?