Tabletop three‐dimensional (3D) display is an attractive display technology that allows multiple individuals around the table to view the reconstructed 3D objects simultaneously, which can be applied to a variety of application scenarios such as desktop conference and board games. In this review paper, the tabletop true 3D display has been characterized and classified into four categories based on the technologies of light field display, integral imaging, and volumetric 3D and holographic 3D displays. Moreover, the comparisons of these technologies are listed, and the prospect of the tabletop 3D display is discussed.
This paper proposes a 360-deg large-scale multiprojection light-field 3D display system, which can reconstruct the light field of models in real space. The reconstructed contents can be observed by multiple viewers from different angles and positions simultaneously. In this system, 360 projectors project images onto a cylindrical light-field diffusion screen whose height is 1.8 m and diameter is 3 m. When moving around the system, viewers can see 3D scenes with smooth-motion parallax, and the frame rate can reach 30 fps and above. To achieve a large-scale display, we design a wide-field lens with cylindrical lenses to enlarge the projection image. To promote efficiency of data transmission and render 3D contents in real time, we apply computers equipped with multiple graphic cards, and display data are divided by field programmable gate array. Finally, a 360-deg light-field autocalibration method based on CCD and multiview sampling is proposed, whose calibration effect is strongly confirmed by experiment results.
Light field (LF) reconstruction is a fundamental technique in light field imaging and has applications in both software and hardware aspects. This paper presents an unsupervised learning method for LF‐oriented view synthesis, which provides a simple solution for generating quality light fields from a sparse set of views. The method is built on disparity estimation and image warping. Specifically, we first use per‐view disparity as a geometry proxy to warp input views to novel views. Then we compensate the occlusion with a network by a forward‐backward warping process. Cycle‐consistency between different views are explored to enable unsupervised learning and accurate synthesis. The method overcomes the drawbacks of fully supervised learning methods that require large labeled training dataset and epipolar plane image based interpolation methods that do not make full use of geometry consistency in LFs. Experimental results demonstrate that the proposed method can generate high quality views for LF, which outperforms unsupervised approaches and is comparable to fully‐supervised approaches.
We proposed a large‐scale multi‐projection light‐field display system, including projectors and a cylindrical diffuser, which is 1.8m high with a radius of 3m. We design a wide‐field projection lens and apply light‐field calibration method based on multi‐view sampling to accurately reconstruct light‐field of models in real space.
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