Paper
19 May 2011 3D integral imaging with unknown sensor positions
Author Affiliations +
Abstract
Integral imaging is a 3D sensing and imaging technique. Conventional 3D integral imaging systems require that all the sensor positions in the image capture stage are known. But in certain image pick up geometries, it may be difficult to obtain accurate measurement of sensor positions such as sensors on moving platforms and/or randomly distributed sensors. In this paper, we present a 3D integral imaging method with unknown sensor positions. In the proposed method, all the sensors are randomly distributed on a plane with parallel optical axes. More, only the relative position of any two sensors is needed whereas all other sensor positions are unknown. We combine image correspondences extraction, camera perspective model, two view geometry and computational integral imaging 3D reconstruction techniques to estimate the unknown sensor positions and reconstruct 3D images. The experiment results executed both in lab and outside show the feasibility of the proposed method in 3D integral imaging. Furthermore, the experiments indicate that the quality of reconstructed images by using the proposed sensor position estimation algorithm can be improved compared to the ones by using the physical measurements of the sensor positions.
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Xiao Xiao, Mehdi Daneshpanah, Myungjin Cho, and Bahram Javidi "3D integral imaging with unknown sensor positions", Proc. SPIE 8043, Three-Dimensional Imaging, Visualization, and Display 2011, 804309 (19 May 2011); https://doi.org/10.1117/12.884283
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KEYWORDS
Sensors

Integral imaging

Cameras

3D image processing

Image sensors

3D image reconstruction

Calibration

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