Skip to main content
SpringerLink
Log in

Real-Time Image and Video Artistic Style Rendering System Based on GPU

  • Conference paper
  • First Online:
Data Science (ICPCSEE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1451))

  • 1034 Accesses

Abstract

Aiming at the practical engineering application of video stylization, in this paper, a GPU-based video art stylization algorithm is proposed, and a real-time video art stylization rendering system is implemented. The four most common artistic styles including cartoon, oil painting, pencil painting and watercolor painting are realized in this system rapidly. Moreover, the system makes good use of the GPU’s parallel computing characteristics, transforms the video stylized rendering algorithm into the texture image rendering process, accelerates the time-consuming pixel traversal processing in parallel and avoids the loop processing of the traditional CPU. Experiments show that the four art styles achieved good results, and the system has a good interactive experience.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Litwinowicz, P.: Processing images and video for an impressionist effect. In: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Technique, pp. 407–414 (1997)

    Google Scholar 

  2. Hertzmann, A., Perlin, K.: Painterly rendering for video and interaction. In: Proceedings of the 1st International Symposium on Non-photorealistic Animation and Rendering (NPAR), pp. 7–12. ACM Press, New York (2000)

    Google Scholar 

  3. Klein, A.W., Grant, T., Cohen, F.: Video mosaics. In: Proceedings of the 2nd International Symposium on Non-photorealistic Animation and Rendering (NPAR), pp. 21–29. ACM Press, New York (2002)

    Google Scholar 

  4. Agarwala, A., Toonz, S.: A semi-automatic approach to creating cel animation from video. In: Proceedings of the 2nd International Symposium on Non-photorealistic Animation and Rendering (NPAR), p. 139. ACM Press, New York (2002)

    Google Scholar 

  5. Agarwala, A., Hertzmann, A., et al.: Keyframe-based tracking for rotoscoping and animation. ACM Trans. Graph. (TOG) 23(3), 584–591. Proceedings of ACM SIGGRAPH 2004 (S0730-0301) (2004)

    Google Scholar 

  6. Wang, J., Xu, Y., et al.: Video tooning. ACM Trans. Graph. (TOG) 23(3), 574–583. Proceedings of ACM SIGGRAPH 2004 (S0730-0301) (2004)

    Google Scholar 

  7. Winnemoeller, H., Olsen, S.C., Gooch, B.: Real-time video abstraction. ACM Transactions on Graphics (TOG) 25(3), 1221–1226. Proceedings of ACM SIGGRAPH 2006 (S1-59593-364-6)

    Google Scholar 

  8. Zhao, Y., Xu, D.: Automatic and real-time video stylization. In: Proceedings of 10th IEEE International Conference on Computer-Aided Design and Computer Graphics, pp. 505–508 (2007). (S978-1-4244-1578-6)

    Google Scholar 

  9. O’Donovan, P., Hertzmann, A.: AniPaint: interactive painterly animation from video. IEEE Trans. Vis. Comput. Graph. 18(3), 475–487 (2012). (S1077-2626)

    Google Scholar 

  10. Wang, Q., Chen, D., Li, S., Wu, Q., Zhang, Q.: An adaptive cartoon-like stylization for color video in real time. Multimedia Tools Appl. 76(15), 16767–16782 (2017)

    Article  Google Scholar 

  11. Kyprianidis, J.E., Kang, H., et al.: Image and video abstraction by anisotropic Kuwahara filtering. Comput. Graph. Forum 28(7), 1955–1963 (2009)

    Google Scholar 

  12. Qiaoyu, W.: Research and implementation of cartoon-like stylization for color video image. J. Huaqiao Univ. Nat. Sci. 35(6), 659–664 (2014)

    Google Scholar 

  13. Geusebroek, J.-M., Smeulders, A.W.M., van de Weijer, J.: Fast anisotropic Gauss filtering. IEEE Trans. Image Process. 12(8), 938–943 (2003)

    Article  MathSciNet  Google Scholar 

  14. Cabral, B., Leedom, L.C.: Imaging vector fields using line integral convolution. In Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques, pp. 263–270 (1993)

    Google Scholar 

  15. Wang, C.-M., Lee, J.-S.: Using ILIC algorithm for an impressionist effect and stylized virtual environments. J. Vis. Lang. Comput. 14, 255–274 (2003)

    Article  Google Scholar 

  16. Yang, Z., Dan, X.: Oil style image generation via fluid simulation. J. Softw. 17(7), 1571–1579 (2006)

    Article  Google Scholar 

  17. Semmo, A., Limberger, D., Kyprianidis, J.E., Döllner, J.: Image stylization by interactive oil paint filtering. Comput. Graph. 55, 1–16 (2016)

    Google Scholar 

  18. Hertzmann, A.: Fast paint texture. In: Proceedings of the 2nd International Symposium on Non-photorealistic Animation and Rendering (NPAR), New York, NY, USA, pp. 91 (2002). (1-58113-494-0)

    Google Scholar 

  19. Wenhua, Q.: Sketch artistic rendering based on significance map. J. Comput.-Aided Des. Comput. Graph. 27(5), 915–923 (2015)

    Google Scholar 

  20. Reinhard, E., Ashikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graphics Appl. 21(5), 34–41 (2001)

    Article  Google Scholar 

  21. Hou, X., Zhang, L., Saliency detection: a spectral residual approach. In: IEEE Conference on Computer Vision & Pattern Recognition, pp. 1–8 (2007)

    Google Scholar 

  22. Hata, M., Toyoura, M., Mao, X.: Automatic generation of accentuated pencil drawing with saliency map and LIC. Vis. Comput. 28(6–8), 657–668 (2012)

    Article  Google Scholar 

  23. Dang ‘en, X., Yang, Z., Dan, X.: A method for generation of pencil filter and its implementation on GPU. J. Comput.-Aided Des. Comput. Graph. 20(1), 26–31 (2008)

    Google Scholar 

  24. Curtis, C.J., Anderson, S.E., et al.: Computer-generated watercolor. In: ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH 1997(0-89791-896-7), pp. 421–430 (1997)

    Google Scholar 

  25. Miaoyi, W., Bin, W., Junhai, Y.: Real-time watercolor illustrations and animation on GPU. J. Graph. 33(3), 73–79 (2012)

    Google Scholar 

  26. Wang, M., Wang, B., Fei, Y., et al.: Towards photo watercolorization with artistic verisimilitude. IEEE Trans. Vis. Comput. Graph. 20(10), 1451–1460 (2014)

    Google Scholar 

  27. Liang, L., Jin, L.: Image-based rendering for ink painting. In: IEEE International Conference on Systems, Man, and Cybernetics, pp. 3950–3954 (2013)

    Google Scholar 

  28. Perona, P., Malik, J.: Scale-space and edge detection using ansotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)

    Google Scholar 

  29. Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 603–619 (2002)

    Google Scholar 

Download references

Acknowledgments

This work is supported by the Natural Science Foundation of China (Grant No.61761046, 62061049), the Application and Foundation Project of Yunnan Province (Grant No.202001BB050032, 202001BB050043, 2018FB100) and the Youth Top Talents Project of Yunnan Provincial “Ten Thousands Plan” (Grant No.YNWR-QNBJ-2018-329).

Author information

Authors and Affiliations

  1. Department of Animation, Yunnan Normal University, Kunming, 650500, China

    Yang Zhao

  2. School of Information Science and Engineering, Yunnan University, Kunming, 650091, China

    Guowu Yuan, Hao Wu, Yuanyuan Pu & Dan Xu

Authors
  1. Yang Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guowu Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hao Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuanyuan Pu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dan Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guowu Yuan .

Editor information

Editors and Affiliations

  1. North University of China, Taiyuan, China

    Jianchao Zeng

  2. North University of China, Taiyuan, China

    Pinle Qin

  3. Northeast Forestry University, Harbin, China

    Weipeng Jing

  4. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  5. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhao, Y., Yuan, G., Wu, H., Pu, Y., Xu, D. (2021). Real-Time Image and Video Artistic Style Rendering System Based on GPU. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2021. Communications in Computer and Information Science, vol 1451. Springer, Singapore. https://doi.org/10.1007/978-981-16-5940-9_24

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-5940-9_24

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5939-3

  • Online ISBN: 978-981-16-5940-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation