Abstract
Effective compression of 3D mesh animation data has been increasingly used in a variety of multimedia systems including virtual reality, gaming, remote transmission, display and storage. In this work, we propose a spectral clustering-based dynamic reshaping model that is performed on spatio-temporal segments to enhance the compression of 3D mesh sequences. After the lossy compression of spatio-temporal segments through Principal Component Analysis (PCA), we first compute a spectral clustering of all the PCA elements. Then, we introduce three novel reshaping schemes (namely, Row-wise matrix scheme, Arch-wise matrix scheme, and Curl-wise matrix scheme) of the PCA elements within each cluster. Through extensive experiments and comparisons, we show our model can substantially improve the compression performances on various 3D mesh sequences.
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References
de Queiroz RL, Chou PA (2016) Compression of 3d point clouds using a region-adaptive hierarchical transform. IEEE Trans Image Process 25 (8):3947–3956
Deutsch P, Gailly JL (1996) Zlib compressed data format specification version 3.3. RFC 1950:1–11
Gandoin PM, Devillers O (2002) Progressive lossless compression of arbitrary simplicial complexes. In: Proceedings of the 29th annual conference on Computer graphics and interactive techniques, vol 21, pp 372–379
Guskov I, Khodakovsky A (2004) Wavelet compression of parametrically coherent mesh sequences. In: Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on computer animation, SCA ’04. Eurographics Association, Goslar, Germany, pp 183–192
Hajizadeh M, Ebrahimnezhad H (2018) Eigenspace compression: dynamic 3d mesh compression by restoring fine geometry to deformed coarse models. Multimed Tools Appl 77(15):19347–19375
Hajizadeh M, Ebrahimnezhad H (2019) Nlme: a nonlinear motion estimation-based compression method for animated mesh sequence. Vis Comput, pp 1–17
Jolliffe IT (1986) Principal components in regression analysis pp 129–155
Karni Z, Gotsman C (2004) Compression of soft-body animation sequences. Comput Graph 28(1):25–34
Khodakovsky A, Schröder P, Sweldens W (2000) Progressive geometry compression. In: Proceedings of the 27th annual conference on Computer graphics and interactive techniques, pp 271–278
Lalos AS, Vasilakis AA, Dimas A, Moustakas K (2017) Adaptive compression of animated meshes by exploiting orthogonal iterations. Vis Comput 33 (6-8):1–11
Lee J, Chai J, Reitsma PSA, Hodgins JK, Pollard NS (2002) Interactive control of avatars animated with human motion data. In: Proceedings of the 29th annual conference on Computer graphics and interactive techniques, vol 21, pp 491–500
Luo G, Deng Z, Zhao X, Jin X, Zeng W, Xie W, Seo H (2020) Spatio-temporal segmentation based adaptive compression of dynamic mesh sequences. ACM Trans Multimedia Comput Commun Appl 16(1):1–24
Maglo A, Grimstead IJ, Hudelot C (2013) Smi 2013: pomar: Compression of progressive oriented meshes accessible randomly. Comput Graph 37 (6):743–752
Maglo A, Lavoué G, Dupont F, Hudelot C (2015) 3d mesh compression: Survey, comparisons, and emerging trends. ACM Comput Surv 47(3):44:1–44:41
Nasiri F, Bidgoli NM, Payan F, Maugey T (2019) A geometry-aware framework for compressing 3d mesh textures. In: ICASSP 2019 - 2019 IEEE International conference on acoustics, speech and signal processing (ICASSP), pp 4015–4019
Pele O, Werman M (2009) Fast and robust earth mover’s distances. In: 2009 IEEE 12Th international conference on computer vision, pp 460–467
Rubner Y, Tomasi C, Guibas LJ (1998) A metric for distributions with applications to image databases. In: Sixth international conference on computer vision (IEEE cat. no 98CH36271), pp 59–66
Sumner RW, Popović J (2004) Deformation transfer for triangle meshes. ACM Trans Graph 23(3):399–405
Valette S, Prost R (2004) Wavelet-based progressive compression scheme for triangle meshes: wavemesh. IEEE Trans Vis Comput Graph 10(2):123–129
Váša L, Skala V (2009) Cobra: Compression of the basis for pca represented animations. Comput Graph Forum 28(6):1529–1540
Váša L, Marras S, Hormann K, Brunnett G (2014) Compressing dynamic meshes with geometric laplacians. Comput Graph Forum 33(2):145–154
Vlasic D, Baran I, Matusik W, Popović J (2008) Articulated mesh animation from multi-view silhouettes. ACM Trans Graph 27(3):97:1–97:9
Acknowledgment
This work has been jointly supported by the National Natural Science Foundation of China under Grant 61962021 and 51978271, the Key Research Program of Jiangxi Province under Grant 20202ACBL202008, the Key Research and Development Program of Jiangxi Province under Grant 20192BBE50079 and the China Postdoctoral Science Foundation under Grant 2020T130264 and 2019M662261 and the Innovation Fund Designated for Graduate Students of Jiangxi Province YC2019-S269.
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Luo, G., Zhao, X., Chen, Q. et al. Dynamic data reshaping for 3D mesh animation compression. Multimed Tools Appl 81, 55–72 (2022). https://doi.org/10.1007/s11042-021-10629-1
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DOI: https://doi.org/10.1007/s11042-021-10629-1