Dual Imaging–Can Virtual Be Better Than Real?
In this paper, a dual imaging technique is used for high-precision reconstruction of an observed 3D scene. In contrast to stereo vision, dual imaging systems use a camera and a projector instead of a camera pair. We propose a multiresolution approach based on the sum-to-one transform, coupled with c...
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doaj-d6094742f81b436da54402f4a423e5392021-03-30T02:44:58ZengIEEEIEEE Access2169-35362020-01-018402464026010.1109/ACCESS.2020.29768709015999Dual Imaging–Can Virtual Be Better Than Real?Ivan Ralasic0https://orcid.org/0000-0003-4479-9099Matea Donlic1https://orcid.org/0000-0001-5165-6438Damir Sersic2https://orcid.org/0000-0001-5008-5047Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, CroatiaIn this paper, a dual imaging technique is used for high-precision reconstruction of an observed 3D scene. In contrast to stereo vision, dual imaging systems use a camera and a projector instead of a camera pair. We propose a multiresolution approach based on the sum-to-one transform, coupled with compressive sensing principles, for efficient estimation of the light transport matrix (LTM). The LTM contains information on both optical systems and the 3D scene. In our setup, the camera sensor is intentionally chosen to be low resolution to prove the future use of inexpensive sensors in nonvisible regions of the light spectrum, as well as the potential design of simplified multiview and light field acquisition systems. We show that a high-precision estimation of the LTM from a reduced set of measurements is possible. Virtual measurements, instead of physical, are conducted to obtain the 3D reconstruction. We show that 3D scene reconstruction from the proposed virtual measurements corresponds with the actual physical acquisition. Moreover, this approach provides much more detail in the reconstruction. The computational complexity of the proposed methods is reduced to such a level that practical implementations are feasible.https://ieeexplore.ieee.org/document/9015999/3D reconstructioncamera-projector systemcompressive sensingdual imaginglight transport |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ivan Ralasic Matea Donlic Damir Sersic |
spellingShingle |
Ivan Ralasic Matea Donlic Damir Sersic Dual Imaging–Can Virtual Be Better Than Real? IEEE Access 3D reconstruction camera-projector system compressive sensing dual imaging light transport |
author_facet |
Ivan Ralasic Matea Donlic Damir Sersic |
author_sort |
Ivan Ralasic |
title |
Dual Imaging–Can Virtual Be Better Than Real? |
title_short |
Dual Imaging–Can Virtual Be Better Than Real? |
title_full |
Dual Imaging–Can Virtual Be Better Than Real? |
title_fullStr |
Dual Imaging–Can Virtual Be Better Than Real? |
title_full_unstemmed |
Dual Imaging–Can Virtual Be Better Than Real? |
title_sort |
dual imaging–can virtual be better than real? |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
In this paper, a dual imaging technique is used for high-precision reconstruction of an observed 3D scene. In contrast to stereo vision, dual imaging systems use a camera and a projector instead of a camera pair. We propose a multiresolution approach based on the sum-to-one transform, coupled with compressive sensing principles, for efficient estimation of the light transport matrix (LTM). The LTM contains information on both optical systems and the 3D scene. In our setup, the camera sensor is intentionally chosen to be low resolution to prove the future use of inexpensive sensors in nonvisible regions of the light spectrum, as well as the potential design of simplified multiview and light field acquisition systems. We show that a high-precision estimation of the LTM from a reduced set of measurements is possible. Virtual measurements, instead of physical, are conducted to obtain the 3D reconstruction. We show that 3D scene reconstruction from the proposed virtual measurements corresponds with the actual physical acquisition. Moreover, this approach provides much more detail in the reconstruction. The computational complexity of the proposed methods is reduced to such a level that practical implementations are feasible. |
topic |
3D reconstruction camera-projector system compressive sensing dual imaging light transport |
url |
https://ieeexplore.ieee.org/document/9015999/ |
work_keys_str_mv |
AT ivanralasic dualimagingx2013canvirtualbebetterthanreal AT mateadonlic dualimagingx2013canvirtualbebetterthanreal AT damirsersic dualimagingx2013canvirtualbebetterthanreal |
_version_ |
1724184680030273536 |