To computer-generate high-quality holographic stereograms, a huge number of images must be provided: several hundred for a horizontal parallax and the square of this number for a full parallax. In this paper, we propose to drastically reduce this number to four input images with depth maps (or equivalently, four groups of neighboring images used to compute a depth map) in any pose, in order to create the missing images with depth image-based rendering. We evaluate the view synthesis method objectively before providing visual results of the corresponding holographic stereograms.
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January 2021
Existing traditional and ConvNet-based methods for light field depth estimation mainly work on the narrow-baseline scenario. This paper explores the feasibility and capability of ConvNets to estimate depth in another promising scenario: wide-baseline light fields. Due to the deficiency of training samples, a large-scale and diverse synthetic wide-baseline dataset with labelled data is introduced for depth prediction tasks.
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December 2020
Multiview video allows for simultaneously presenting dynamic imaging from multiple viewpoints, enabling a broad range of immersive applications. This paper proposes a novel super-resolution (SR) approach to mixed-resolution (MR) multiview video, whereby the low-resolution (LR) videos produced by MR camera setups are up-sampled based on the neighboring HR videos. Our solution analyzes the statistical correlation of different resolutions between multiple views, and introduces a low-rank prior based SR optimization framework using local linear embedding and weighted nuclear norm minimization.
View Article and Find Full Text PDFRecent advances in the creation of microlens arrays as holographic optical elements allow the creation of projector-based see-through light field displays suitable for augmented reality. These systems require an accurate calibration of the projector with relation to the microlens array, as any small misalignment causes the 3D reconstruction to fail. The methods reported so far require precise placement of the calibration camera w.
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May 2014
We present a novel scale-invariant image feature detection algorithm (D-SIFER) using a newly proposed scale-space optimal 10th-order Gaussian derivative (GDO-10) filter, which reaches the jointly optimal Heisenberg's uncertainty of its impulse response in scale and space simultaneously (i.e., we minimize the maximum of the two moments).
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September 2012
In this brief, we present a constant time method for the joint bilateral filtering. First, we propose an image data structure, coined as joint integral histograms (JIHs). Extending the classic integral images and the integral histograms, it represents the global information of two correlated images.
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