3D Mosaic from Images

Ji Hun Park

doi:10.4028/www.scientific.net/AMM.752-753.1081

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 752-7533D Mosaic from Images

3D Mosaic from Images

Abstract:

This paper presents a tool for 3D object mosaic. Given a set of background removed input images, we first compute a 3D reconstructed volumetric model body using shape from silhouette. The granularity of a volumetric body is the user input. Voxel center coordinates, voxel color, and surface normal of the voxel are computed for 3D mosaic. The voxels of reconstructed volumetric body are replaced by primitive shapes such as sphere, cylinder, cone, etc. We call this process as a 3D mosaic. The background-eliminated input images may contain information on body parts supplied by a user. Using information on body parts, only a part of 3D reconstructed volumetric body is replaced by a new shape while the rest of body retains voxel information. The surface normal values are used for primitive shapes with direction such as a cone. 3D mosaic can be used for emphasizing or deemphasizing a part of 3D reconstructed model body, similar to the function of a 2D image mosaic. Emphasizing and deemphasizing is done by resolution, surface normal, size of body parts, color and/or shape of the 3D primitive object.

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Periodical:

Applied Mechanics and Materials (Volumes 752-753)

Pages:

1081-1084

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.752-753.1081

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Online since:

April 2015

Authors:

Ji Hun Park*

Keywords:

3D Mosaic, 3D Volumetric Reconstruction, Camera Calibration, Surface Deformation

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References

[1] R. Hartleya and A. Zisserman, Multiple View Geometry in Computer Vision, second ed., Cambridge University Press, Cambridge, (2004).

Google Scholar

[2] L. Lasdon, A. Warren, A. Jain and M. Ratner, Design and testing of a generalized reduced gradient code for nonlinear programming, ACM Trans. Math. Software, 4 (1978) 34-50.

DOI: 10.1145/355769.355773

Google Scholar

[3] D. Lowe, Distinctive image features from scale-invariant keyponts, Int. J. of Comput. Vision, 60 (2004) 91-110.

Google Scholar

[4] T. Moons, L.V. Gool and M. Vergauwen, 3D reconstruction from multiple images, part I: Principles, Found. and Trends in Comput. Graphics and Vision, 4 (2008) 287-404.

DOI: 10.1561/0600000007

Google Scholar

[5] J. Park and S. Park, Improvement on Zhang's camera calibration, App. Mech. Mater. 479-480 (2013) 479-480.

Google Scholar

[6] Z. Zhang, A flexible new technique for camera calibration, IEEE Trans. Patt. Anal. Mach. Intel. 22 (2000) 1330-1334.

Google Scholar