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http://dx.doi.org/10.3837/tiis.2019.06.019

Palette-based Color Attribute Compression for Point Cloud Data  

Cui, Li (Department of Computer & Software, Hanyang University)
Jang, Euee S. (Department of Computer & Software, Hanyang University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.6, 2019 , pp. 3108-3120 More about this Journal
Abstract
Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.
Keywords
Point cloud; palette color; clustering; spatial redundancy; color attribute compression;
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1 J. B. Kim and H. S. Jun, "Vision-based location positioning using Augmented Reality for Indoor navigation," IEEE Trans. on Consumer Electronics, vol. 54, no. 3, pp. 954-962, Aug. 2008.   DOI
2 H. Heo, E. C. Lee, K. R. Park, C. J. Kim, and M. C. Whang, "A realistic game system using multi-modal user interfaces," IEEE Trans. on Consumer Electronics, vol. 56, no. 3, pp. 1364-1372, Aug. 2010.   DOI
3 J. Peng, C. S. Kim and C. C. Jay Kuo, "Technologies for 3D mesh compression: A survey," J. Visual Communication Image Representation, vol. 16, no. 6, pp. 688-733, Dec. 2005.   DOI
4 A. Maglo, G. Lavoue, F. Dupont, and C. Hudelot, "3D mesh compression: Survey, Comparisons and Emerging Trends," ACM Comput. Surv., vol. 47, no. 3, pp. 44:1-44:41, Feb. 2015.
5 M. Deering, "Geometry Compression," in Proc. of SIGGRAPH '95, pp. 13-20, 1995.
6 D. Y. Lee, S. B. Sull, and C. S. Kim, "Progressive 3D mesh compression using MOG-based Bayesian entropy coding and gradual prediction," The Visual Computer, vol. 30, no. 10, pp. 1077-1091, Mar. 2014.   DOI
7 F. Caillaud, V. Vidal, F. Dupont, and G. Lavoue, "Progressive compression of arbitrary textured meshes," Computer Graphics Forum, vol. 35, no. 7, pp. 475-484, Oct. 2016.   DOI
8 L. Vasa, S. Marras, K. Hormann, and G. Brunnett, "Compressing dynamic meshes with geometric Laplacians," Computer Graphics Forum, vol. 33, no. 2, pp. 145-154, May 2014.
9 R. L. de Queiroz and P. A. Chou, "Transform coding for point clouds using a gaussian process model," IEEE Trans. Image Process., vol. 26, no. 7, pp. 3507-3517, July 2017.   DOI
10 D. Thanou, P. A. Chou and P. Frossard, "Graph-based compression of dynamic 3D point cloud sequences," IEEE Trans. Image Process., vol. 25, no. 4, pp. 1765-1778, April 2016.   DOI
11 "Specifications for $Xperia^{TM}$ XZ1," Sonymobile.com. [Online].
12 "iPhone-X tech specs," Apple.com. [Online].
13 Millen Yanachkov, "Huawei P11 may feature a camera that rivals Apple's TrueDepth system on the iPhoneX," Phonearena.com, 2017. [Online].
14 "Qualcomm First to Announce Depth-sensing Camera Technology Designed for Android Ecosystem," Qualcomm.com, 2017. [Online].
15 R. L. de Queiroz and P. A. Chou, "Motion-compensated compression of dynamic voxelized point clouds," IEEE Trans. Image Process., vol. 26, no. 8, pp. 3886-3895, Aug. 2017.   DOI
16 A. Anis, P. A. Chou and A. Ortega, "Compression of dynamic 3D point clouds using subdivisional meshes and graph wavelet transforms," in Proc. of IEEE ICASSP, pp.6360-6364, 2016.
17 Y. Fan, Y. Huang, and J. Peng, "Point cloud compression based on hierarchical point clustering," in Proc. of IEEE SIPAASC, Kaohsiung, pp. 1-7, 2013.
18 J. Kammerl, N. Blodow, R. B. Rusu, S. Gedikli, M. Beetz, and E. Steinbach, "Real-time compression of Point Cloud Streams," in Proc. of IEEE ICRA, Saint Paul, MN, pp. 778-785, 2012.
19 K. Ainala, R. N. Mekuria, B. Khathariya, Z. Li, Y. K. Wang, and R. Joshi, "An improved enhancement layer for octree based point cloud compression with plane projection approximation," in Proc. of ADIP, pp.22-25, 2016.
20 R. A. Cohen, D. Tian, and A. Vetro, "Point cloud attribute compression using 3D intra prediction and shape-adaptive transforms," in Proc. of IEEE DCC, USA, pp. 141-150, 2016.
21 C. Zhang, D. Florencio and C. Loop, "Point cloud attribute compression with graph transform," in Proc. of IEEE ICIP, Paris, pp. 2066-2070, 2014.
22 R. A. Cohen, D. Tian and A. Vetro, "Attribute compression for sparse point clouds using graph transforms," in Proc. of IEEE ICIP, pp. 1374-1378, 2016.
23 P. A. Chou, and R. L. de Queirioz, "Gaussian process transforms," in Proc. of IEEE ICIP, Phoenix, AZ, pp. 1524-1528, 2016.
24 R. L. de Queiroz and P. A. Chou, "Compression of 3d point clouds using a region-adaptive hierarchical transform," IEEE Trans. Image Process., vol. 25, no. 8, pp. 3947-3956, Aug. 2016.   DOI
25 R. Mekuria, K. Blom and P. Cesar, "Design, implementation and evaluation of a point cloud codec for tele-immersive video," IEEE Trans. Circuits and Systems for Video Technology, vol. 27, no. 4, pp. 828-842, April 2017.   DOI
26 L. Cui, H. Y. Xu, and E. S. Jang, "Hybrid color attribute compression for point cloud data," in Proc. of IEEE ICME, Hong Kong, pp. 1273-1278, 2017.