Paper
7 March 2013 Plenoptic depth map in the case of occlusions
Zhan Yu, Jingyi Yu, Andrew Lumsdaine, Todor Georgiev
Author Affiliations +
Proceedings Volume 8667, Multimedia Content and Mobile Devices; 86671S (2013) https://doi.org/10.1117/12.2005847
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Recent realizations of hand-held plenoptic cameras have given rise to previously unexplored effects in photography. Designing a mobile phone plenoptic camera is becoming feasible with the significant increase of computing power of mobile devices and the introduction of System on a Chip. However, capturing high numbers of views is still impractical due to special requirements such as ultra-thin camera and low costs. In this paper, we analyze a mobile plenoptic camera solution with a small number of views. Such a camera can produce a refocusable high resolution final image if a depth map is generated for every pixel in the sparse set of views. With the captured multi-view images, the obstacle to recovering a high-resolution depth is occlusions. To robustly resolve these, we first analyze the behavior of pixels in such situations. We show that even under severe occlusion, one can still distinguish different depth layers based on statistics. We estimate the depth of each pixel by discretizing the space in the scene and conducting plane sweeping. Specifically, for each given depth, we gather all corresponding pixels from other views and model the in-focus pixels as a Gaussian distribution. We show how it is possible to distinguish occlusion pixels, and in-focus pixels in order to find the depths. Final depth maps are computed in real scenes captured by a mobile plenoptic camera.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhan Yu, Jingyi Yu, Andrew Lumsdaine, and Todor Georgiev "Plenoptic depth map in the case of occlusions", Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86671S (7 March 2013); https://doi.org/10.1117/12.2005847
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Cited by 5 scholarly publications.
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KEYWORDS
Cameras

Image resolution

Image processing

Sensors

Statistical analysis

Translucency

Image restoration

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