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The real-world applications of 3D point clouds have been growing rapidly in recent years, but not much effective work has been dedicated to perceptual quality assessment of colored 3D point clouds.
G. Turk and M. Levoy, “Zippered polygon meshes from range images,” in Proc. ACM SIGGRAPH . ACM, 1994, pp. 311–318
1994
Earlier work this paper cites.
P. Cignoni, C. Rocchini, and R. Scopigno, “Metro: measuring error on simplified surfaces,” in Computer Graphics Forum , vol. 17, no. 2. Wiley Online Library, 1998, pp. 167–174
1998
Earlier work this paper cites.
Z. Wang, E. Simoncelli, and A. Bovik, “Multiscale structural similarity for image quality assessment,” in Proc. IEEE Asilomar Conf. on Signals, Systems, and Computers . IEEE, 2003, pp. 1398–1402
2003
Earlier work this paper cites.
Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Processing , vol. 13, no. 4, pp. 600–612, April 2004
2004
Earlier work this paper cites.
L. C. H. R. Sheikh, A. C. Bovik and Z. Wang. (2005) LIVE image quality assessment database. [Online]. Available: http://live.ece.utexas.edu/research/Quality/subjective.htm
2005
Earlier work this paper cites.
H. R. Sheikh, M. F. Sabir, and A. C. Bovik, “A statistical evaluation of recent full reference image quality assessment algorithms,” IEEE Trans. Image Processing , vol. 15, no. 11, pp. 3440–3451, November 2006
2006
Earlier work this paper cites.
H. Sheikh and A. Bovik, “Image information and visual quality,” IEEE Trans. Image Processing , vol. 15, no. 2, pp. 430–444, February 2006
2006
Earlier work this paper cites.
S. Sharples, S. Cobb, A. Moody, and J. R. Wilson, “Virtual reality induced symptoms and effects (VRISE): Comparison of head mounted display (HMD), desktop and projection display systems,” Displays , vol. 29, no. 2, pp. 58–69, 2008
2008
Earlier work this paper cites.
P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, and G. Ranzuglia, “Meshlab: an open-source mesh processing tool,” in Eurographics Italian Chapter Conference , 2008, pp. 129–136
2008
Earlier work this paper cites.
Z. Wang and A. C. Bovik, “Mean squared error: love it or leave it? A new look at signal fidelity measures,” IEEE Signal Processing Magazine , vol. 26, no. 1, pp. 98–117, 2009
2009
Earlier work this paper cites.
R. B. Rusu and S. Cousins, “3D is here: Point cloud library (PCL),” in Proc. IEEE Int. Conf. Robotics and Automation . IEEE, 2011, pp. 1–4
2011
Earlier work this paper cites.
Z. Wang and Q. Li, “Information content weighting for perceptual image quality assessment,” IEEE Trans. Image Processing , vol. 20, no. 5, pp. 1185–1198, May 2011
2011
Earlier work this paper cites.
ITU, “Methodology for the subjective assessment of the quality of television pictures,” Recommendation BT. 500-13 , 2012
2012
Earlier work this paper cites.
A. G. Solimini, “Are there side effects to watching 3D movies? a prospective crossover observational study on visually induced motion sickness,” PloS One , vol. 8, no. 2, 2013
2013
Earlier work this paper cites.
M. Kazhdan and H. Hoppe, “Screened poisson surface reconstruction,” ACM Trans. Graphics , vol. 32, no. 3, pp. 29:1–29:13, June 2013
2013
Earlier work this paper cites.
J. Zhang, W. Huang, X. Zhu, and J.-N. Hwang, “A subjective quality evaluation for 3D point cloud models,” in Proc. IEEE Int. Conf. Audio, Language and Image Processing . IEEE, 2014, pp. 827–831
2014
Earlier work this paper cites.
D. C. Montgomery and G. C. Runger, Applied statistics and probability for engineers . John Wiley and Sons, 2014
2014
Earlier work this paper cites.
G. Lavoué, M. C. Larabi, and L. Váša, “On the efficiency of image metrics for evaluating the visual quality of 3D models,” IEEE Trans. Visualization and Computer Graphics , vol. 22, no. 8, pp. 1987–1999, August 2015
2015
Earlier work this paper cites.
R. Mekuria, Z. Li, C. Tulvan, and P. Chou, “Evaluation criteria for PCC (point cloud compression),” ISO/IEC JTC1/SC29/WG11 MPEG, N16332 , 2016
2016
Earlier work this paper cites.
C. Loop, Q. Cai, S. O. Escolano, and P. A. Chou, “Microsoft voxelized upper bodies-a voxelized point cloud dataset,” ISO/IEC JTC1/SC29 Joint WG11/WG1 (MPEG/JPEG) input document m38673/M72012 , 2016
2016
Earlier work this paper cites.
A. Javaheri, C. Brites, F. Pereira, and J. Ascenso, “Subjective and objective quality evaluation of 3D point cloud denoising algorithms,” in Proc. IEEE Int. Conf. Multimedia and Expo Workshops . IEEE, 2017, pp. 1–6
2017
Earlier work this paper cites.
E. Alexiou and T. Ebrahimi, “On subjective and objective quality evaluation of point cloud geometry,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience . IEEE, 2017, pp. 1–3
2017
Earlier work this paper cites.
A. Javaheri, C. Brites, F. Pereira, and J. Ascenso, “Subjective and objective quality evaluation of compressed point clouds,” in Proc. IEEE Int. Workshop on Multimedia Signal Processing . IEEE, 2017, pp. 1–6
2017
Earlier work this paper cites.
E. Alexiou and T. Ebrahimi, “On the performance of metrics to predict quality in point cloud representations,” in Applications of Digital Image Processing XL , vol. 10396. Int. Society for Optics and Photonics, 2017, pp. 103 961H:301–103 961H:317
2017
Earlier work this paper cites.
E. Alexiou, E. Upenik, and T. Ebrahimi, “Towards subjective quality assessment of point cloud imaging in augmented reality,” in Proc. IEEE Int. Workshop on Multimedia Signal Processing . IEEE, 2017, pp. 1–6
2017
Earlier work this paper cites.
D. Tian, H. Ochimizu, C. Feng, R. Cohen, and A. Vetro, “Geometric distortion metrics for point cloud compression,” in Proc. IEEE Int. Conf. Image Processing , 2017, pp. 3460–3464
2017
Earlier work this paper cites.
——, “Evaluation metrics for point cloud compression,” ISO/IEC JTC1/SC29/WG11 MPEG, M39966 , 2017
2017
Earlier work this paper cites.
——, “Updates and integration of evaluation metric software for PCC,” ISO/IEC JTC1/SC29/WG11 MPEG, M40522 , 2017
2017
Earlier work this paper cites.
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
2017
Earlier work this paper cites.
E. d’Eon, B. Harrison, T. Myers, and P. Chou, “8i voxelized full bodies-a voxelized point cloud dataset,” ISO/IEC JTC1/SC29 Joint WG11/WG1 (MPEG/JPEG) input document WG11M40059/WG1M74006, Geneva , 2017
2017
Earlier work this paper cites.
——, “PCC test model category 2 v0,” ISO/IEC JTC1/SC29/WG11 MPEG, N17248 , 2017
2017
Earlier work this paper cites.
C. Guede, J. Ricard, S. Lasserre, and J. Llach, “Technicolor point cloud renderer,” ISO/IEC JTC1/SC29/WG11 MPEG, N16902 , 2017
2017
Cited alongside, same era.
E. Alexiou, T. Ebrahimi, M. Bernardo, M. Pereira, A. Pinheiro, L. da Silva Cruz, C. Duarte, L. Dmitrovic, E. Dumic, D. Matkovic, and A. Skodras, “Point cloud subjective evaluation methodology based on 2D rendering,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience . IEEE, 2018, pp. 1–6
2018
Cited alongside, same era.
E. Alexiou, A. Pinheiro, C. Duarte, D. Matkovic, E. Dumic, L. da Silva Cruz, L. Dmitrovic, M. Bernardo, M. Pereira, and T. Ebrahimi, “Point cloud subjective evaluation methodology based on reconstructed surfaces,” in Proc. SPIE Optical Engineering+Applications . SPIE, 2018, pp. 107 520H.1–107 520H.14
2018
Cited alongside, same era.
E. M. Torlig, E. Alexiou, T. A. Fonseca, R. L. de Queiroz, and T. Ebrahimi, “A novel methodology for quality assessment of voxelized point clouds,” in Applications of Digital Image Processing XLI , vol. 10752. International Society for Optics and Photonics, 2018, p. 107520I
E. Alexiou, N. Yang, and T. Ebrahimi, “PointXR: A toolbox for visualization and subjective evaluation of point clouds in virtual reality,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience , no. CONF, 2020
2020
Later among the works it cites.
G. Meynet, Y. Nehmé, J. Digne, and G. Lavoué, “PCQM: A full-reference quality metric for colored 3D point clouds,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience , 2020
2020
Later among the works it cites.
I. Viola, S. Subramanyam, and P. César, “A color-based objective quality metric for point cloud contents,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience , 2020
2020
Later among the works it cites.
A. Javaheri, C. Brites, F. Pereira, and J. Ascenso, “Improving PSNR-based quality metrics performance for point cloud geometry,” in Proc. IEEE Int. Conf. Image Processing . IEEE, 2020, pp. 3438–3442
2020
Later among the works it cites.
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2018
Cited alongside, same era.
E. Alexiou and T. Ebrahimi, “Point cloud quality assessment metric based on angular similarity,” in Proc. IEEE Int. Conf. Multimedia and Expo . IEEE, 2018, pp. 1–6
2018
Cited alongside, same era.
——, “Impact of visualization strategy for subjective quality assessment of point clouds,” in Proc. IEEE Int. Conf. Multimedia and Expo Workshops . IEEE, 2018, pp. 1–6
2018
Cited alongside, same era.
——, “Benchmarking of objective quality metrics for colorless point clouds,” in Proc. IEEE Picture Coding Symposium . IEEE, 2018, pp. 51–55
2018
Cited alongside, same era.
E. Dumic, C. R. Duarte, and L. A. da Silva Cruz, “Subjective evaluation and objective measures for point clouds—state of the art,” in Int. Colloquium on Smart Grid Metrology (SmaGriMet) . IEEE, 2018, pp. 1–5
2018
Cited alongside, same era.
S. Schwarz, M. Preda, V. Baroncini, M. Budagavi, P. Cesar, P. A. Chou, R. A. Cohen, M. Krivokuća, S. Lasserre, Z. Li et al. , “Emerging MPEG standards for point cloud compression,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems , vol. 9, no. 1, pp. 133–148, 2018
2018
Cited alongside, same era.
MPEG, “MPEG point cloud datasets,” http://mpegfs.int-evry.fr/MPEG/PCC/DataSets/pointCloud/CfP/datasets
2018
Cited alongside, same era.
JPEG, “JPEG Pleno database,” https://jpeg.org/plenodb
2018
Cited alongside, same era.
Agisoft, “Agisoft Photoscan,” http://www.agisoft.com
2018
Cited alongside, same era.
——, “Mahalanobis based point to distribution metric for point cloud geometry quality evaluation,” IEEE Signal Processing Letters , vol. 27, pp. 1350–1354, 2020
2020
Later among the works it cites.
I. Viola and P. Cesar, “A reduced reference metric for visual quality evaluation of point cloud contents,” IEEE Signal Processing Letters , 2020
2020
Later among the works it cites.
K. Cao, Y. Xu, and P. Cosman, “Visual quality of compressed mesh and point cloud sequences,” IEEE Access , vol. 8, pp. 171 203–171 217, 2020
2020
Later among the works it cites.
Q. Yang, Z. Ma, Y. Xu, Z. Li, and J. Sun, “Inferring point cloud quality via graph similarity,” IEEE Trans. Pattern Analysis and Machine Intelligence , 2020
2020
Later among the works it cites.
Q. Yang, H. Chen, Z. Ma, Y. Xu, R. Tang, and J. Sun, “Predicting the perceptual quality of point cloud: A 3D-to-2D projection-based exploration,” IEEE Trans. Multimedia , 2020
2020
Later among the works it cites.
R. Diniz, P. G. Freitas, and M. C. Farias, “Multi-distance point cloud quality assessment,” in Proc. IEEE Int. Conf. Image Processing . IEEE, 2020, pp. 3443–3447
2020
Later among the works it cites.
——, “Towards a point cloud quality assessment model using local binary patterns,” in Proc. IEEE Int. Conf. Quality of Multimedia Experience . IEEE, 2020, pp. 1–6
2020
Later among the works it cites.
S. Perry, H. P. Cong, L. A. da Silva Cruz, J. Prazeres, M. Pereira, A. Pinheiro, E. Dumic, E. Alexiou, and T. Ebrahimi, “Quality evaluation of static point clouds encoded using MPEG codecs,” in Proc. IEEE Int. Conf. Image Processing . IEEE, 2020, pp. 3428–3432
2020
Later among the works it cites.
R. Diniz, P. G. Freitas, and M. C. Farias, “Local luminance patterns for point cloud quality assessment,” in Proc. IEEE Int. Workshop on Multimedia Signal Processing . IEEE, 2020, pp. 1–6
2020
Later among the works it cites.
L. Hua, M. Yu, G. Jiang, Z. He, and Y. Lin, “VQA-CPC: a novel visual quality assessment metric of color point clouds,” in Optoelectronic Imaging and Multimedia Technology VII , vol. 11550. International Society for Optics and Photonics, 2020, p. 1155012
2020
Later among the works it cites.
2020
Later among the works it cites.
J. Gutiérrez, T. Vigier, and P. L. Callet, “Quality evaluation of 3D objects in mixed reality for different lighting conditions,” Electronic Imaging , vol. 2020, no. 11, pp. 128–1, 2020
2020
Later among the works it cites.
Y. Nehmé, F. Dupont, J.-P. Farrugia, P. Le Callet, and G. Lavoué, “Visual quality of 3D meshes with diffuse colors in virtual reality: Subjective and objective evaluation,” IEEE Trans. Visualization and Computer Graphics , 2020
2020
Later among the works it cites.
S. Ye, D. Chen, S. Han, Z. Wan, and J. Liao, “Meta-pu: An arbitrary-scale upsampling network for point cloud,” IEEE Trans. Visualization and Computer Graphics , 2021
2021
Closest in time.
X. Zhao, B. Zhang, J. Wu, R. Hu, and T. Komura, “Relationship-based point cloud completion,” IEEE Trans. Visualization and Computer Graphics , 2021
2021
Closest in time.
Q. Liu, H. Yuan, R. Hamzaoui, H. Su, J. Hou, and H. Yang, “Reduced reference perceptual quality model with application to rate control for video-based point cloud compression,” IEEE Trans. Image Processing , vol. 30, pp. 6623–6636, 2021
2021
Closest in time.
E. Dumic, F. Battisti, M. Carli, and L. A. da Silva Cruz, “Point cloud visualization methods: a study on subjective preferences,” in 28th European Signal Processing Conference (EUSIPCO) . IEEE, 2021, pp. 595–599
2021
Closest in time.
L. Hua, M. Yu, Z. He, R. Tu, and G. Jiang, “CPC-GSCT: Visual quality assessment for coloured point cloud based on geometric segmentation and colour transformation,” IET Image Processing , 2021
2021
Closest in time.
R. Diniz, P. G. Freitas, and M. Farias, “A novel point cloud quality assessment metric based on perceptual color distance patterns,” Electronic Imaging , vol. 2021, no. 9, pp. 256–1, 2021
2021
Closest in time.
X. Wu, Y. Zhang, C. Fan, J. Hou, and S. Kwong, “Subjective quality database and objective study of compressed point clouds with 6dof head-mounted display,” IEEE Trans. Circuits and Systems for Video Technology , 2021
2021
Closest in time.
Z. He, G. Jiang, Z. Jiang, and M. Yu, “Towards a colored point cloud quality assessment method using colored texture and curvature projection,” in Proc. IEEE Int. Conf. Image Processing . IEEE, 2021, pp. 1444–1448
2021
Closest in time.
R. Diniz, M. Q. Farias, and P. Garcia-Freitas, “Color and geometry texture descriptors for point-cloud quality assessment,” IEEE Signal Processing Letters , 2021
2021
Closest in time.
L. Hua, G. Jiang, M. Yu, and Z. He, “Bqe-cvp: Blind quality evaluator for colored point cloud based on visual perception,” in 2021 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) . IEEE, 2021, pp. 1–6
2021
Closest in time.
W.-x. Tao, G.-y. Jiang, Z.-d. Jiang, and M. Yu, “Point cloud projection and multi-scale feature fusion network based blind quality assessment for colored point clouds,” in Proc. ACM Int. Conf. Multimedia , 2021, pp. 5266–5272
2021
Closest in time.
Y. Xu, Q. Yang, L. Yang, and J.-N. Hwang, “Epes: Point cloud quality modeling using elastic potential energy similarity,” IEEE Transactions on Broadcasting , 2021
2021
Closest in time.
Y. Zhang, Q. Yang, and Y. Xu, “Ms-graphsim: Inferring point cloud quality via multiscale graph similarity,” in Proc. ACM Int. Conf. Multimedia , 2021, pp. 1230–1238
2021
Closest in time.