Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service

A sequence of 3D models generated using volumetric capture has the advantage of retaining the characteristics of dynamic objects and scenes. However, in volumetric data, since 3D mesh and texture are synthesized for every frame, the mesh of every frame has a different shape, and the brightness and c...

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Main Authors: Byung-Seo Park, Sol Lee, Jung-Tak Park, Jin-Kyum Kim, Woosuk Kim, Young-Ho Seo
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/22/8815
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author Byung-Seo Park
Sol Lee
Jung-Tak Park
Jin-Kyum Kim
Woosuk Kim
Young-Ho Seo
author_facet Byung-Seo Park
Sol Lee
Jung-Tak Park
Jin-Kyum Kim
Woosuk Kim
Young-Ho Seo
author_sort Byung-Seo Park
collection DOAJ
description A sequence of 3D models generated using volumetric capture has the advantage of retaining the characteristics of dynamic objects and scenes. However, in volumetric data, since 3D mesh and texture are synthesized for every frame, the mesh of every frame has a different shape, and the brightness and color quality of the texture is various. This paper proposes an algorithm to consistently create a mesh of 4D volumetric data using dynamic reconstruction. The proposed algorithm comprises remeshing, correspondence searching, and target frame reconstruction by key frame deformation. We make non-rigid deformation possible by applying the surface deformation method of the key frame. Finally, we propose a method of compressing the target frame using the target frame reconstructed using the key frame with error rates of up to 98.88% and at least 20.39% compared to previous studies. The experimental results show the proposed method’s effectiveness by measuring the geometric error between the deformed key frame and the target frame. Further, by calculating the residual between two frames, the ratio of data transmitted is measured to show a compression performance of 18.48%.
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spelling doaj.art-33cc230fbbbf4c9097a6edb479d07a9c2023-11-24T09:56:14ZengMDPI AGSensors1424-82202022-11-012222881510.3390/s22228815Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming ServiceByung-Seo Park0Sol Lee1Jung-Tak Park2Jin-Kyum Kim3Woosuk Kim4Young-Ho Seo5Department of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaDepartment of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaDepartment of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaDepartment of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaDepartment of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaDepartment of Electronic Materials Engeering, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Republic of KoreaA sequence of 3D models generated using volumetric capture has the advantage of retaining the characteristics of dynamic objects and scenes. However, in volumetric data, since 3D mesh and texture are synthesized for every frame, the mesh of every frame has a different shape, and the brightness and color quality of the texture is various. This paper proposes an algorithm to consistently create a mesh of 4D volumetric data using dynamic reconstruction. The proposed algorithm comprises remeshing, correspondence searching, and target frame reconstruction by key frame deformation. We make non-rigid deformation possible by applying the surface deformation method of the key frame. Finally, we propose a method of compressing the target frame using the target frame reconstructed using the key frame with error rates of up to 98.88% and at least 20.39% compared to previous studies. The experimental results show the proposed method’s effectiveness by measuring the geometric error between the deformed key frame and the target frame. Further, by calculating the residual between two frames, the ratio of data transmitted is measured to show a compression performance of 18.48%.https://www.mdpi.com/1424-8220/22/22/88154D volumetricremeshingcorrespondencedynamic reconstructionmesh compression
spellingShingle Byung-Seo Park
Sol Lee
Jung-Tak Park
Jin-Kyum Kim
Woosuk Kim
Young-Ho Seo
Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
Sensors
4D volumetric
remeshing
correspondence
dynamic reconstruction
mesh compression
title Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
title_full Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
title_fullStr Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
title_full_unstemmed Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
title_short Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service
title_sort dynamic reconstruction and mesh compression of 4d volumetric model using correspondence based deformation for streaming service
topic 4D volumetric
remeshing
correspondence
dynamic reconstruction
mesh compression
url https://www.mdpi.com/1424-8220/22/22/8815
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