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International Conference on Intelligent Systems Design and Applications

ISDA 2020: Intelligent Systems Design and Applications pp 128–139Cite as

A Locally Weighted Metric for Measuring the Perceptual Quality of 3D Objects

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

Abstract

The increasing use of 3D models in many areas lead us to think about the impact of the different distortions that can affect the 3D object during the rendering process. These deformations are usually evaluated using geometric metrics, which have not a good correlation with human judgment, while the visual perceptual quality of 3D models is necessary. In this context, a new full-reference metric denoted LWRMS is defined in this work. It can predict the distortion score between the original object and its damaged version without taking into account the constraint of connectivity. The proposed metric is defined in order to get a good correlation with the human visual perception coming from a subjective measurement. The numerical experiments are carried out on a known database LIRIS/EPFL General-Purpose database. The quantitative results show a good performance of the proposed metric in comparison with methods from the literature.

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References

  1. Agathos, A., Azariadis, P.: 3D reconstruction of skeletal mesh models and human foot biomodel generation using semantic parametric-based deformation. Int. J. Comput. Appl. 42(2), 127–140 (2020)

    Google Scholar 

  2. Aspert, N., Santa-Cruz, D., Ebrahimi, T.: Mesh: Measuring errors between surfaces using the hausdorff distance. In: Proceedings. IEEE International Conference on Multimedia and Expo, vol. 1, pp. 705–708. IEEE (2002)

    Google Scholar 

  3. Booth, J., Roussos, A., Ponniah, A., Dunaway, D., Zafeiriou, S.: Large scale 3D morphable models. Int. J. Comput. Vision 126(2–4), 233–254 (2018)

    Article  MathSciNet  Google Scholar 

  4. Bulbul, A., Capin, T., Lavoué, G., Preda, M.: Assessing visual quality of 3-D polygonal models. IEEE Signal Process. Mag. 28(6), 80–90 (2011)

    Article  Google Scholar 

  5. Chen, M.J., Su, C.C., Kwon, D.K., Cormack, L.K., Bovik, A.C.: Full-reference quality assessment of stereopairs accounting for rivalry. Signal Process. Image Commun. 28(9), 1143–1155 (2013)

    Article  Google Scholar 

  6. Cignoni, P., Rocchini, C., Scopigno, R.: Metro: measuring error on simplified surfaces. In: Computer Graphics Forum, vol. 17, pp. 167–174. Wiley Online Library (1998)

    Google Scholar 

  7. Corsini, M., Gelasca, E.D., Ebrahimi, T., Barni, M.: Watermarked 3-D mesh quality assessment. IEEE Trans. Multimedia 9(2), 247–256 (2007)

    Article  Google Scholar 

  8. Elloumi, N., Kacem, H.L.H., Bouhlel, M.S.: The efficiency of perceptual quality metrics 3D meshes based on the human visual system. In: International Workshop Soft Computing Applications, pp. 497–508. Springer (2016)

    Google Scholar 

  9. Elloumi, N., Kacem, H.L.H., Bouhlel, M.S.: Quality metric of 3d models using weber’s law. In: Eleventh International Conference on Machine Vision (ICMV 2018), vol. 11041, p. 110410B. International Society for Optics and Photonics (2019)

    Google Scholar 

  10. Elloumi, N., Kacem, H.L.H., Dey, N., Ashour, A.S., Bouhlel, M.S.: Perceptual metrics quality: Comparative study for 3d static meshes. Int. J. Serv. Sci. Manage. Eng. Technol (IJSSMET) 8(1), 63–80 (2017)

    Google Scholar 

  11. Gelasca, E.D., Ebrahimi, T., Corsini, M., Barni, M.: Objective evaluation of the perceptual quality of 3d watermarking. In: IEEE International Conference on Image Processing 2005, vol. 1, pp. I–241. IEEE (2005)

    Google Scholar 

  12. Hewage, C.T., Martini, M.G.: Reduced-reference quality assessment for 3D video compression and transmission. IEEE Trans. Consum. Electron. 57(3), 1185–1193 (2011)

    Article  Google Scholar 

  13. Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 11, 1254–1259 (1998)

    Article  Google Scholar 

  14. Izadi, S., Kim, D., Hilliges, O., Molyneaux, D., Newcombe, R., Kohli, P., Shotton, J., Hodges, S., Freeman, D., Davison, A., et al.: Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 559–568. ACM (2011)

    Google Scholar 

  15. JG, T., Wolff, A., Torres, J., My, H.T.: Usability evaluation of the interactive 3D virtual reality cultural heritage museum display: Fountain of the lions software application. Int. J. Eng. Technol. 7(2.28), 95–99 (2018)

    Google Scholar 

  16. Karni, Z., Gotsman, C.: Spectral compression of mesh geometry. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, pp. 279–286. ACM Press/Addison-Wesley Publishing Co. (2000)

    Google Scholar 

  17. Kaur, A., Sidhu, J.S., Bhullar, J.S.: Adaptive deblocking technique based on separate modes for removing compression effects in jpeg coded images. International Journal of Computers and Applications pp. 1–13 (2019)

    Google Scholar 

  18. Lavoué, G.: A multiscale metric for 3d mesh visual quality assessment. In: Computer Graphics Forum. vol. 30, pp. 1427–1437. Wiley Online Library (2011)

    Google Scholar 

  19. Lavoué, G., Corsini, M.: A comparison of perceptually-based metrics for objective evaluation of geometry processing. IEEE Trans. Multimedia 12(7), 636–649 (2010)

    Article  Google Scholar 

  20. Lavoué, G., Gelasca, E.D., Dupont, F., Baskurt, A., Ebrahimi, T.: Perceptually driven 3d distance metrics with application to watermarking. In: Applications of Digital Image Processing XXIX. vol. 6312, p. 63120L. International Society for Optics and Photonics (2006)

    Google Scholar 

  21. McNamara, A., Mania, K., Banks, M., Healey, C.: Perceptually-motivated graphics, visualization and 3d displays. In: ACM SIGGRAPH 2010 Courses. p. 7. ACM (2010)

    Google Scholar 

  22. Pérez-Lantero, P.: Area and perimeter of the convex hull of stochastic points. Comput. J. 59(8), 1144–1154 (2016)

    Article  MathSciNet  Google Scholar 

  23. Reddy, M.: Perceptually optimized 3d graphics. IEEE Comput. Graphics Appl. 21(5), 68–75 (2001)

    Article  Google Scholar 

  24. Ryu, S., Sohn, K.: No-reference quality assessment for stereoscopic images based on binocular quality perception. IEEE Trans. Circuits Syst. Video Technol. 24(4), 591–602 (2013)

    Google Scholar 

  25. Sorkine, O., Cohen-Or, D., Toledo, S.: High-pass quantization for mesh encoding. In: Symposium on Geometry Processing. vol. 42 (2003)

    Google Scholar 

  26. Vasa, L., Skala, V.: A perception correlated comparison method for dynamic meshes. IEEE Trans. Visual Comput. Graphics 17(2), 220–230 (2010)

    Article  Google Scholar 

  27. Zhu, Q., Zhao, J., Du, Z., Zhang, Y.: Quantitative analysis of discrete 3d geometrical detail levels based on perceptual metric. Computers & Graphics 34(1), 55–65 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mines Saint-Etienne, CNRS, UMR 5307 LGF, Centre SPIN 158 cours Fauriel, 42023 SAINT-ETIENNE Cedex 2, Saint-Étienne, France

    Johan Debayle

  2. University of Sfax, ISBS, UR SETIT, 3038, Sfax, Tunisia

    Habiba Loukil & Med Salim Bouhlel

  3. University of Sousse, ISITCom, 4011, Sousse, Tunisia

    Nessrine Elloumi

Authors
  1. Nessrine Elloumi
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  2. Johan Debayle
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  3. Habiba Loukil
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  4. Med Salim Bouhlel
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Cite this paper

Elloumi, N., Debayle, J., Loukil, H., Bouhlel, M.S. (2021). A Locally Weighted Metric for Measuring the Perceptual Quality of 3D Objects. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_12

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