Central Angle Optimization for 360-degree Holographic 3D Content

• URL: http://arxiv.org/abs/2311.05878v1
• Date: Fri, 10 Nov 2023 05:30:43 GMT
• Title: Central Angle Optimization for 360-degree Holographic 3D Content
• Authors: Hakdong Kim, Minsung Yoon, and Cheongwon Kim
• Abstract summary: In this study, we propose a method to find an optimal central angle in deep learning-based depth map estimation. We experimentally demonstrate and discuss the relationship between the central angle and the quality of digital holographic content.
• Score: 3.072340427031969
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this study, we propose a method to find an optimal central angle in deep learning-based depth map estimation used to produce realistic holographic content. The acquisition of RGB-depth map images as detailed as possible must be performed to generate holograms of high quality, despite the high computational cost. Therefore, we introduce a novel pipeline designed to analyze various values of central angles between adjacent camera viewpoints equidistant from the origin of an object-centered environment. Then we propose the optimal central angle to generate high-quality holographic content. The proposed pipeline comprises key steps such as comparing estimated depth maps and comparing reconstructed CGHs (Computer-Generated Holograms) from RGB images and estimated depth maps. We experimentally demonstrate and discuss the relationship between the central angle and the quality of digital holographic content.

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