Abstract / truncated to 115 words (read the full abstract)

This thesis discusses approaches and techniques to convert Sparsely-Sampled Light Fields (SSLFs) into Densely-Sampled Light Fields (DSLFs), which can be used for visualization on 3DTV and Virtual Reality (VR) devices. Exemplarily, a movable 1D large-scale light field acquisition system for capturing SSLFs in real-world environments is evaluated. This system consists of 24 sparsely placed RGB cameras and two Kinect V2 sensors. The real-world SSLF data captured with this setup can be leveraged to reconstruct real-world DSLFs. To this end, three challenging problems require to be solved for this system: (i) how to estimate the rigid transformation from the coordinate system of a Kinect V2 to the coordinate system of an RGB camera; (ii) how to ... toggle 8 keywords

camera calibration sparsely-sampled light field acquisition densely-sampled light field reconstruction light field angular super-resolution novel view synthesis epipolar-plane image inpainting shearlet transform self-supervised learning


Gao, Yuan
Department of Computer Science, Kiel University
Publication Year
Upload Date
Aug. 26, 2020

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