3D Integral Imaging Using Sparse Sensors With Unknown Positions
In this paper, the 3D integral imaging method is extended to situations where the sensor positions in the image pick up stage are unknown. Conventional integral imaging systems require a priori knowledge of sensor positions in the image capture stage which can be difficult to measure in synthetic ap...
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Published in | Journal of display technology Vol. 6; no. 12; pp. 614 - 619 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.12.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 1551-319X 1558-9323 |
DOI | 10.1109/JDT.2010.2070485 |
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Abstract | In this paper, the 3D integral imaging method is extended to situations where the sensor positions in the image pick up stage are unknown. Conventional integral imaging systems require a priori knowledge of sensor positions in the image capture stage which can be difficult to measure in synthetic aperture or randomly distributed sensors modes. In the proposed method, only the relative position of two sensors is needed whereas all other sensors positions are unknown. We combine image correspondences extraction, camera perspective model, two view geometry and computational integral imaging 3D reconstruction techniques to overcome this limitation in integral imaging systems. The image reconstruction quality of the system with unknown sensor positions is compared with conventional integral imaging with known sensor positions. We also demonstrate how the proposed method may be used to improve the image reconstruction quality even in situations where the sensor positions recorded are subject to measurement errors . |
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AbstractList | In this paper, the 3D integral imaging method is extended to situations where the sensor positions in the image pick up stage are unknown. Conventional integral imaging systems require a priori knowledge of sensor positions in the image capture stage which can be difficult to measure in synthetic aperture or randomly distributed sensors modes. In the proposed method, only the relative position of two sensors is needed whereas all other sensors positions are unknown. We combine image correspondences extraction, camera perspective model, two view geometry and computational integral imaging 3D reconstruction techniques to overcome this limitation in integral imaging systems. The image reconstruction quality of the system with unknown sensor positions is compared with conventional integral imaging with known sensor positions. We also demonstrate how the proposed method may be used to improve the image reconstruction quality even in situations where the sensor positions recorded are subject to measurement errors . |
Author | Myungjin Cho Xiao Xiao DaneshPanah, Mehdi Javidi, Bahram |
Author_xml | – sequence: 1 surname: Xiao Xiao fullname: Xiao Xiao email: xiao.2.xiao@uconn.edu organization: Electr. & Comput. Eng. Dept., Univ. of Connecticut, Storrs, CT, USA – sequence: 2 givenname: Mehdi surname: DaneshPanah fullname: DaneshPanah, Mehdi email: mehdi@engr.uconn.edu organization: Electr. & Comput. Eng. Dept., Univ. of Connecticut, Storrs, CT, USA – sequence: 3 surname: Myungjin Cho fullname: Myungjin Cho email: yammako@engr.uconn.edu organization: Electr. & Comput. Eng. Dept., Univ. of Connecticut, Storrs, CT, USA – sequence: 4 givenname: Bahram surname: Javidi fullname: Javidi, Bahram email: bahram.javidi@uconn.edu organization: Electr. & Comput. Eng. Dept., Univ. of Connecticut, Storrs, CT, USA |
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SubjectTerms | 3D reconstruction image Cameras Display devices Image reconstruction Image sensors Imaging Integral imaging Integrals Mathematical models plane camera calibration Position measurement Sensors Studies Three dimensional Three dimensional displays unknown sensor position |
Title | 3D Integral Imaging Using Sparse Sensors With Unknown Positions |
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