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Efficient immersive video coding using specular detection for high rendering quality

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Abstract

Previous 2D video coding standards obtain efficient compression of traditional 2D color images. However, because new services, such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), have been recently introduced, an immersive video coding standard that compresses view information captured at many viewpoints is being actively developed for high immersion of VR, AR, and MR. This video coding standard generates patches, which represent non-overlap** areas among different views. In general, the patches give a high impact on rendering of specular areas in virtual viewpoints, but it is very difficult to accurately find them. Therefore, this paper proposes an efficient immersive video coding method using specular detection for high rendering quality, which generates additional specular patches. Experimental results demonstrate that the proposed method improves the rendering quality in terms of specularity with a negligible change in coding performance. In particular, subjective assessments clearly show the effectiveness of the proposed method.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

This work was supported in prat by the Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (IITP-2024-RS-2022-00156345, IITP-2017-0-00072) and in prat by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2023-00219051).

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Authors and Affiliations

  1. Department of Intelligent Mechatronics Engineering, Sejong University, Seoul, Republic of Korea

    Yongho Choi, The Van Le & ** Young Lee

  2. Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea

    Gun Bang & **ho Lee

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  1. Yongho Choi
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Correspondence to ** Young Lee.

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Choi, Y., Van Le, T., Bang, G. et al. Efficient immersive video coding using specular detection for high rendering quality. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18815-7

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