CTDP Depacking with Guided Depth Upsampling Networks for Realization of Multiview 3D Video

Wei Jong Yang, Bo Xun Chen, Jar Ferr Yang

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

With the advancement of 3D display technology, the original 3D stereo-view systems requiring 3D glasses have evolved to multiple-view naked-eyes 3D displays. For 2D broadcasting systems, we can pack one view and its corresponding depth map into a frame in the transmission side and generate multiple views by the depth image-based rendering (DIBR) engine at the receivers. Up to now, the centralized texture depth packing (CTDP) frame-compatible format is the best solution for view and depth packing. In this paper, we propose an improved CTDP depacking method and realize it with DIBR process to achieve real-time 3D multiview exhibition. To maintain the quality of the depacked depth map, in the CTDP depacking process, we suggest a deep learning-based guided depth upsampling network. The experimental results demonstrate that the proposed 3D multiview system can successfully depack CTDP video and generate 9-view 3D movies in real-time. The proposed guided depth upsampling network achieves a better quality of the generated views than the traditional algorithms.

原文English
主出版物標題Advances in Information and Communication - Proceedings of the 2023 Future of Information and Communication Conference, FICC 2023
編輯Kohei Arai
發行者Springer Science and Business Media Deutschland GmbH
頁面136-152
頁數17
ISBN(列印)9783031280757
DOIs
出版狀態Published - 2023
事件8th Future of Information and Computing Conference, FICC 2023 - Virtual, Online
持續時間: 2023 3月 22023 3月 3

出版系列

名字Lecture Notes in Networks and Systems
651 LNNS
ISSN(列印)2367-3370
ISSN(電子)2367-3389

Conference

Conference8th Future of Information and Computing Conference, FICC 2023
城市Virtual, Online
期間23-03-0223-03-03

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 訊號處理
  • 電腦網路與通信

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