Advertisement

Multimedia Tools and Applications

, Volume 71, Issue 1, pp 279–292 | Cite as

Pointillist video stylization based on particle tracing

  • SangHyun SeoEmail author
  • Victor Ostromoukhov
Article

Abstract

We present an algorithm that stylizes an input video into a painterly animation without user intervention. In particular, we focus on pointillist animation with stable temporal coherence. Temporal coherence is an important problem in non-photorealistic rendering for videos. To realize pointillist animation, the various characters of pointillism should be considered in painting process to maintain temporal coherence. For this, weused the particle video algorithm which is a new approach to long-range motion estimation in video. Based on this method, we introduce a method to control the density of particles considering the features of frames and importance maps. Finally, the propagation methods of stroke to minimize flickering effects of brush strokes are introduced.

Keywords

Non-photorealistic rendering and animation Video stylization Pointillist animation Temporal coherence 

Notes

Acknowledgements

This work was supported by the Korea Research Foundation Grant funded by the Korean Government (KRF-2011-357-D00202) and was partly supported by French institutional grant AMCQMCSGA ANR-10-CEXC-002.

References

  1. 1.
    Gossett N, Chen B (2004) Paint inspired color mixing and compositing for visualization. In: INFOVIS ’04: Proceedings of the IEEE symposium on information visualization, pp 113–118Google Scholar
  2. 2.
    Haeberli P (1990) Paint by numbers: Abstract image representations. ACM SIGGRAPH Comput Graph 24(4):207–214. doi:10.1145/97880.97902 CrossRefGoogle Scholar
  3. 3.
    Hays J, Essa I (2004) Image and video based painterly animation. In: Proc. NPAR’04, pp 113–120Google Scholar
  4. 4.
    Hertzmann A (1998) Painterly rendering with curved brush strokes of multiple sizes. In: Proc. SIGGRAPH’98, pp 453–460Google Scholar
  5. 5.
    Hertzmann A (2001) Paint by relaxation. In: Computer graphics international’01, pp 47–54Google Scholar
  6. 6.
    Hertzmann A, Perlin K (2000) Painterly rendering for video and interaction. In: Proceedings of the 1st international symposium on non-photorealistic animation and rendering, NPAR ’00. ACM, New York, pp 7–12CrossRefGoogle Scholar
  7. 7.
    Hua Huang LZ, Fu TN (2010) Video painting via motion layer manipulation. Comput Graph Forum 29(7):2055–2064CrossRefGoogle Scholar
  8. 8.
    Kagaya M, Brendel W, Deng Q, Kesterson T, Todorovic S, Neill PJ, Zhang E (2011) Video painting with space-time-varying style parameters. IEEE Trans Vis Comput Graph 17(1):74–87. doi:10.1109/TVCG.2010.25 CrossRefGoogle Scholar
  9. 9.
    Kang H, Lee S, Chui CK (2007) Coherent line drawing. In: In Proc. non-photorealistic animation and rendering, pp 43–50Google Scholar
  10. 10.
    Lee H, Seo S, Ryoo S, Ahn K, Yoon K (2012) A multi-level depiction method for painterly rendering based on visual perception cue. Multimed Tools Appl 1–16. doi:10.1007/s11042-012-1036-x Google Scholar
  11. 11.
    Lin L, Zeng K, Lv H, Wang Y, Xu Y, Zhu SC (2010) Painterly animation using video semantics and feature correspondence. In: Proceedings of the 8th international symposium on non-photorealistic animation and rendering, NPAR ’10. ACM, New York, pp 73–80Google Scholar
  12. 12.
    Litwinowicz PC (1997) Processing images and video for an impressionist effect. In: Proc. SIGGRAPH’97, pp 407–414Google Scholar
  13. 13.
    Meier BJ (1996) Painterly rendering for animation. In: In SIGGRAPH 96 conference proceedings, pp 477–484Google Scholar
  14. 14.
    O’Donovan P, Hertzmann A (2012) Anipaint: interactive painterly animation from video. IEEE Trans Vis Comput Graph 18(3):475–487. doi:10.1109/TVCG.2011.51 CrossRefGoogle Scholar
  15. 15.
    Park Y, Yoon K (2008) Painterly animation using motion maps. Graph Models 70(1–2):1–15CrossRefMathSciNetGoogle Scholar
  16. 16.
    Sand P, Teller S (2008) Particle video: Long-range motion estimation using point trajectories. Int J Comput Vis 80(1):72–91. doi: 10.1007/s11263-008-0136-6 CrossRefGoogle Scholar
  17. 17.
    Schwarz M, Stamminger M (2009) On predicting visual popping in dynamic scenes. In: Proceedings of the 6th symposium on applied perception in graphics and visualization, APGV ’09. ACM, New York, pp 93–100. doi:10.1145/1620993.1621012 CrossRefGoogle Scholar
  18. 18.
    Seo S, Yoon K (2010) Color juxtaposition for pointillism based on an artistic color model and a statistical analysis. Vis Comput 26(6–8):421–431CrossRefGoogle Scholar
  19. 19.
    Seo S, Ryoo S, Park J (2011) Interactive painterly rendering with artistic error correction. Multimed Tools Appl 1–17. doi: 10.1007/s11042-011-0796-z Google Scholar
  20. 20.
    Yantis S, Jonides J (1984) Abrupt visual onsets and selective attention: evidence from visual search. J Exp Psychol Hum Percept Perform 10:601–621CrossRefGoogle Scholar
  21. 21.
    Zhao M, Zhu SC (2011) Customizing painterly rendering styles using stroke processes. In: Collomosse JP, Asente P, Spencer SN (eds) NPAR. ACM, New York, pp 137–146Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.LIRISLyon 1 UniversityLyonFrance

Personalised recommendations