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Face-off: automatic alteration of facial features

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Abstract

Pursuing or maintaining beautifulness nowadays has become a trend in modern society, especially among the celebrity community. In some cases, one may choose to adopt drastic procedures to alter his or her facial or body features to achieve the desired beauty, thus the blossom of industry on cosmetic plastic surgeries. In addition, people whose faces got damaged due to accidental burns or wounds may also find these surgeries necessary. However, as performing the related surgeries are still considered intrusive and costly, it is better to “preview” the result before a surgery is actually carried out. As many believe that facial appearance matters most, we have developed a system that allows a user to input a photo and changes the associated individual facial feature in an automatic and user-friendly manner. Overall speaking, our system makes contributions in the following four aspects. First, our system not only offers the previewing functionality, but also allows users to interactively fine-tune the desired results, thus making it a useful companion tool for facial cosmetic surgeries. Second, instead of exchanging the overall look of a face, as being done by some existing approaches, our system offers much finer granularity by allowing each and every facial feature to be changed individually and independently, thus achieving higher face-off flexibility. Third, while existing tools generally entail manual effort to locate or align facial features, our system, through the help of Active Shape Model or ASM for short, characterized by a scheme of automatic feature extraction, eliminates most of the needs of user assistance. Finally, for convenience, we have constructed a database of facial features to facilitate the facial feature alteration process. To justify our claims, we have rendered results and compared them with those from existing approaches to demonstrate the effectiveness of our system. We have also conducted a user study to further confirm the usefulness of such a system.

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References

  1. Adelson EH, Anderson CH, Bergen JR, Burt PJ, Ogden JM (1984) Pyramid method in image processing. RCA Eng 29(6):33–41

    Google Scholar 

  2. Agarwala A, Dontcheva M, Agrawala M, Drucker S, Colburn A, Curless B, Salesin D, Cohen M (2004) Interactive digital photomontage. In: SIGGRAPH ’2004, pp 294–302

  3. Bertalmio M, Sapiro G, Caselles V, Ballester C (2000) Image inpainting. In: SIGGRAPH ’2000

  4. Bitouk D, Kumar N, Dhilon S, Belhumeur P, Nayar SK (2008) Face swapping: automatically replacing faces in photographs. In: SIGGRAPH ’2008

  5. Blanz V, Scherbaum K, Vetter T, Seidel H (2004) Exchanging faces in images. In: Eurographics ’2004

  6. Blanz V, Vetter T (1999) A morphable model for the synthesis of 3D faces. In: SIGGRAPH ’1999

  7. Bornard R, Lecan E, Laborelli L, Chenot J (2002) Missing data correction in still images and image sequences. In: ACM multimedia ’2002, pp 355–361

  8. Boykov Y, Jolly MP (2001) Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In: ICCV ’2001

  9. Cootes T, Taylor CJ, Cooper DH, Graham J (1995) Active shape models—their training and application. Comput Vis Image Underst 61(1):38–59

    Article  Google Scholar 

  10. Cootes TF, Taylor CJ (2001) Statistical models of appearance for medical image analysis and computer vision. In: Proc. SPIE medical imaging, pp 236–248

  11. Efros AA, Leung TK (1999) Texture synthesis by non-parametric sampling. In: ICCV ’99

  12. Gu H, Su G, Du C (2003) Feature points extraction from faces. In: Image and vision computing. NZ

  13. Jia J, Sun J, Tang C, Shum H (2006) Drag-and-drop pasting. In: SIGGRAPH ’2006, pp 631–637

  14. Kjeldsen R, Kender J (1996) Finding skin in color images. In: FG’ 96 (2nd international conference on automatic face and gesture recognition)

  15. Kwatra V, Schodl A, Essa I, Bobick A (2003) Graphcut textures: image and video synthesis using graph cuts. In: SIGGRAPH ’2003

  16. Lalonde J, Hoiem D, Efros AA, Rother C, Winn J, Criminisi A (2007) Photo clip art. In: SIGGRAPH ’2007

  17. Levin A, Zomet A, Peleg S, Weiss Y (2004) Seamless image stitching in the gradient domain. In: ECCV ’2004, pp 377–389

  18. Leyvand T, Cohen-Or D, Dror G, Lischinski D (2006) Digital face beautification. In: SIGGRAPH 2006 technical sketch

  19. Leyvand T, Cohen-Or D, Dror G, Lischinski D (2008) Data-driven enhancement of facial attractiveness. In: SIGGRAPH ’2008

  20. Mortensen EN, Barrett WA (1995) Intelligent scissors for image composition. In: SIGGRAPH ’1995, pp 191–198

  21. Oliveira MM, Bowen B, McKenna R, Chang Y (2001) Fast digital image inpainting. In: VIIP (International conference on visualization, imaging and image processing) ’2001

  22. Peleg S (1981) Elimination seams from photomosaics. In: Conference on pattern recognition and image processing, pp 426–429

  23. Perez P, Gangnet M, Blake A (2003) Poisson image editing. In: SIGGRAPH ’2003, pp 313–318

  24. Sun J, Yuan L, Jia J, Shum H (2005) Image completion with structural propagation. In: SIGGRAPH ’2005, pp 861–868

  25. Uyttendaele M, Eden A, Szeliski R (2001) Eliminating ghosting and exposure artifacts in image mosaics. In: CVPR ’2001, pp 509–516

  26. Wang J, Agrawala M, Cohen M (2007) Soft scissors: an interactive tool for realtime high quality matting. In: SIGGRAPH ’2007

  27. Wei L, Levoy M (2000) Fast texture synthesis using tree-structured vector quantization. In: SIGGRAPH ’2000, pp 479–488

  28. Yang C, Chiang W (2008) An interactive facial expression generation system. Multimed Tools Appl 40(1):41–60

    Article  Google Scholar 

  29. Yang M, Kriegman DJ, Ahuja N (2002) Detecting faces in images: a survey. IEEE Trans Pattern Anal Mach Intell 24(1):34–58

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Information Management, National Taiwan University of Science and Technology, No. 43, Sec. 4, Keelung Road, Taipei, 106, Taiwan, Republic of China

    Jia-Kai Chou, Chuan-Kai Yang & Sing-Dong Gong

Authors
  1. Jia-Kai Chou
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  2. Chuan-Kai Yang
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  3. Sing-Dong Gong
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Correspondence to Chuan-Kai Yang.

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Chou, JK., Yang, CK. & Gong, SD. Face-off: automatic alteration of facial features. Multimed Tools Appl 56, 569–596 (2012). https://doi.org/10.1007/s11042-010-0624-x

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  • DOI: https://doi.org/10.1007/s11042-010-0624-x

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