Skip to main content
Log in

A survey on face modeling: building a bridge between face analysis and synthesis

  • Survey
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Face modeling refers to modeling the shape and appearance of human faces which lays the basis for model-based facial analysis, synthesis and animation. This paper summarizes the existing state-of-the-art work on face modeling and animation in the Computer Graphics and the Computer Vision areas. While some models or techniques are exclusively used for facial analysis or for facial animation and synthesis, other models combine analysis and synthesis in an analysis-by-synthesis loop. This paper introduces a taxonomy of face modeling methods in function of the area of application (synthesis and analysis) and builds a link between the two by reviewing analysis-by-synthesis face modeling methods. The interest of such a taxonomy is to introduce new face models that combine ideas from the analysis and synthesis domains. We also provide an overview of the extensions of the seminal works presented in this paper. Within each category, we discuss the advantages and disadvantages of each method with respect to the others.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28

Similar content being viewed by others

References

  1. C++ implementation of deva ramanan’s articulated pose estimation with flexible mixtures of parts”articulated pose estimation with flexible mixtures-of-parts. https://github.com/wg-perception/PartsBasedDetector

  2. Eigenfaces implementation. https://github.com/agyorev/Eigenfaces

  3. Abboud, B., Davoine, F.: Bilinear factorisation for facial expression analysis and synthesis. Vision, image and signal processing. IEE Proc. 152(3), 327–333 (2005)

    Article  Google Scholar 

  4. Ahlberg, J.: Candide-3–an updated parameterized face. Tech. rep., Report No. LiTH-ISY, Dept. of Electrical Engineering. Linkoping University, Sweden (2001)

  5. Ahlberg, J.: An active model for facial feature tracking. EURASIP J. Appl. Signal Process. 2002(1), 566–571 (2002)

    Google Scholar 

  6. Aldrian, O., Smith, W.A.: Inverse rendering of faces with a 3D morphable model. IEEE Trans. Pattern Anal. Mach. Intell. 35(5), 1080–1093 (2013)

    Article  Google Scholar 

  7. Ayala-Raggi, S., Altamirano-Robles, L., Cruz-Enriquez, J.: Automatic face interpretation using fast 3D illumination-based AAM models. Comput. Vis. Image Underst. 115(2), 194–210 (2011)

    Article  Google Scholar 

  8. Bacivarov, I.: Advances in the modelling of facial sub-regions and facial expressions using active appearance techniques. Ph.D. thesis, National University of Ireland, College of Engineering and Informatics (2009)

  9. Bagherian, E., Rahmat, R.W.O.: Facial feature extraction for face recognition: a review. In: 2008 IEEE International Symposium on Information Technology, vol. 2, pp. 1–9 (2008)

  10. Bailly, K.: Méthodes d’apprentissage pour l’estimation de la pose de la tête dans des images monoculaires. Ph.D. thesis, Université Pierre et Marie Curie-Paris VI (2010)

  11. Baizhen, Z., Qiuqi, R.: Facial feature extraction using improved deformable templates. In: IEEE 8th International Conference on Signal processing, vol. 4 (2006)

  12. Baltrušaitis, T., Robinson, P., Morency, L.P.: 3D constrained local model for rigid and non-rigid facial tracking. In: IEEE Conference on Computer vision and pattern recognition (CVPR), pp. 2610–2617 (2012)

  13. Baran, I., Popovic, J.: Automatic rigging and animation of 3D characters. ACM Trans. on Graph. (TOG) 26(3), 72 (2007)

    Article  Google Scholar 

  14. Basso, C., Vetter, T., Blanz, V.: Regularized 3D morphable models. In: First IEEE International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis, 2003. HLK 2003, pp. 3–10 (2003)

  15. Batur, A., Hayes, M.: Adaptive active appearance models. IEEE Trans. Image Process. 14(11), 1707–1721 (2005)

    Article  Google Scholar 

  16. Blake, A., Curwen, R., Zisserman, A.: Affine-invariant contour tracking with automatic control of spatiotemporal scale. In: Proceedings. IEEE Fourth International Conference on Computer Vision, pp. 66–75 (1993)

  17. Blake, A., Isard, M.: Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion, 1st edn. Springer, Secaucus (1998)

    Book  Google Scholar 

  18. Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: Proceedings of the 26th annual conference on Computer graphics and interactive techniques, pp. 187–194 (1999)

  19. Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE Trans. Pattern Anal. Machine Intell. 25(9), 1063–1074 (2003)

    Article  Google Scholar 

  20. Canzler, U., Kraiss, K.: Person-adaptive facial feature analysis for an advanced wheelchair user-interface. Conf. Mechatron. Robot. 3, 871–876 (2004)

    Google Scholar 

  21. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. Int. J. Comput. Vis. 22(1), 61–79 (1997)

    Article  MATH  Google Scholar 

  22. Caunce, A., Taylor, C., Cootes, T.: Adding facial actions into 3d model search to analyse behaviour in an unconstrained environment. In: Advances in Visual Computing, pp. 132–142. Springer, Berlin (2010)

  23. Caunce, A., Taylor, C., Cootes, T.: Using detailed independent 3D sub-models to improve facial feature localisation and pose estimation. In: Advances in Visual Computing, pp. 398–408. Springer, Berlin (2012)

  24. Çeliktutan, O., Ulukaya, S., Sankur, B.: A comparative study of face landmarking techniques. EURASIP J. Image Video Process. 2013(1), 13 (2013)

    Article  Google Scholar 

  25. Cesar, R., Bengoetxea, E., Bloch, I.: Inexact graph matching using stochastic optimization techniques for facial feature recognition. In: Pattern Recognition, 2002. Proceedings. IEEE 16th International Conference on, vol. 2, pp. 465–468 (2002)

  26. Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Image Process. 10(2), 266–277 (2001)

    Article  MATH  Google Scholar 

  27. Cootes, T., Cooper, D., Taylor, C., Graham, J.: Trainable method of parametric shape description. Image and Vision Comput. 10(5), 289–294 (1992)

    Article  Google Scholar 

  28. Cootes, T., Edwards, G., Taylor, C.: Active appearance models. In: IEEE European Conference on Computer Vision (ECCV ’98), p. 484 (1998)

  29. Cootes, T., Edwards, G., Taylor, C.: A comparative evaluation of active appearance model algorithms. Br. Mach. Vis. Conf. 2, 680–689 (1998)

    Google Scholar 

  30. Cootes, T., Taylor, C.: A mixture model for representing shape variation. Image Vis. Comput. 17(8), 567–573 (1999)

    Article  Google Scholar 

  31. Cootes, T., Taylor, C.: An algorithm for tuning an active appearance model to new data. In: Proc. British Machine Vision Conference, vol. 3, pp. 919–928. Citeseer (2006)

  32. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape models-their training and application. Computer Vis. Image Underst. 61(1), 38–59 (1995)

    Article  Google Scholar 

  33. Cordea, M., Petriu, E., Petriu, D.: Three-dimensional head tracking and facial expression recovery using an anthropometric muscle-based active appearance model. IEEE Trans. Instrum. Meas. 57(8), 1578–1588 (2008)

    Article  Google Scholar 

  34. Cristinacce, D., Cootes, T.: A comparison of shape constrained facial feature detectors. In: Proceedings, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 375–380 (2004)

  35. Cristinacce, D., Cootes, T.: Facial feature detection and tracking with automatic template selection. In: Automatic Face and Gesture Recognition, 2006. FGR 2006. 7th International Conference on, pp. 429–434. IEEE (2006)

  36. Cristinacce, D., Cootes, T.: Feature detection and tracking with constrained local models. Proc. Br. Mach. Vis. Conf. 3, 929–938 (2006)

    MATH  Google Scholar 

  37. Cristinacce, D., Cootes, T.: Boosted regression active shape models. Proc. Br. Mach. Vis. Conf. 2, 880–889 (2007)

    Google Scholar 

  38. Cristinacce, D., Cootes, T.: Automatic feature localisation with constrained local models. Pattern Recognit. 41(10), 3054–3067 (2008)

    Article  MATH  Google Scholar 

  39. Ding, C., Choi, J., Tao, D., Davis, L.S.: Multi-directional multi-level dual-cross patterns for robust face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 38(3), 518–531 (2016)

    Article  Google Scholar 

  40. Donner, R., Reiter, M., Langs, G., Peloschek, P., Bischof, H.: Fast active appearance model search using canonical correlation analysis. IEEE Trans. Pattern Anal. Mach. Intell. 28(10), 1690–1694 (2006)

    Article  Google Scholar 

  41. Dornaika, F., Davoine, F.: Head and facial animation tracking using appearance-adaptive models and particle filters. In: Conference on Computer Vision and Pattern Recognition Workshop, 2004. CVPRW’04. pp. 153–153 (2004)

  42. Dornaika, F., Davoine, F.: On appearance based face and facial action tracking. IEEE Trans. Circuits Syst. Video Technol. 16(9), 1107–1124 (2006)

    Article  Google Scholar 

  43. Ekman, P., Friesen, W.: Facial Action Coding System. Consulting Psychologists Press, Palo Alto (1977)

    Google Scholar 

  44. Eleftheriadis, A., Herpel, C., Rajan, G., Ward, L.: Mpeg-4 systems, text for iso/iec fcd 14496-1 systems. Tech. rep., MPEG-4 SNHC (1998)

  45. Ersotelos, N., Dong, F.: Building highly realistic facial modeling and animation: a survey. Vis. Comput. 24(1), 13–30 (2008)

    Article  Google Scholar 

  46. Essa, I., Basu, S., Darrell, T., Pentland, A.: Modeling, tracking and interactive animation of faces and heads using input from video. In: Proceedings, IEEE Computer Animation’96, pp. 68–79 (1996)

  47. Felzenszwalb, P., Huttenlocher, D.: Pictorial structures for object recognition. Int. J. Comput. Vis. 61(1), 55–79 (2005)

    Article  Google Scholar 

  48. Feng, W., Kim, B., Yu, Y.: Real-time data driven deformation using kernel canonical correlation analysis. ACM Trans. Gr. (TOG) 27(3), 91 (2008)

    Google Scholar 

  49. Fischler, M.A., Elschlager, R.A.: The representation and matching of pictorial structures. IEEE Trans. Comput. 100(22) (1973)

  50. Gao, X., Su, Y., Li, X., Tao, D.: Gabor texture in active appearance models. Neurocomputing 72(13), 3174–3181 (2009)

    Article  Google Scholar 

  51. Gao, X., Su, Y., Li, X., Tao, D.: A review of active appearance models. IEEE Trans. Syst., Man, Cybern., Part C: Appl. Rev. 40(2), 145–158 (2010)

    Article  Google Scholar 

  52. Gast, E., Lew, M.: A framework for real-time face and facial feature tracking using optical flow pre-estimation and template tracking. Master’s thesis, LIACS, Leiden University (2010)

  53. Gibson, S.F., Mirtich, B.: A survey of deformable modeling in computer graphics. Tech. rep, Citeseer (1997)

  54. Glasbey, C., Mardia, K.: A review of image-warping methods. J. Appl. Stat. 25(2), 155–171 (1998)

    Article  MATH  Google Scholar 

  55. Goldenberg, R., Kimmel, R., Rivlin, E., Rudzsky, M.: Fast geodesic active contours. IEEE Trans. Image Process. 10(10), 1467–1475 (2001)

    Article  MathSciNet  Google Scholar 

  56. Gonzalez-Mora, J., De la Torre, F., Murthi, R., Guil, N., Zapata, E.: Bilinear active appearance models. In: IEEE 11th International Conference on Computer Vision, 2007. ICCV, pp. 1–8 (2007)

  57. Graciano, A., Cesar Jr., R., Bloch, I.: Inexact graph matching for facial feature segmentation and recognition in video sequences: results on face tracking. In: Progress in Pattern Recognition, Speech and Image Analysis, pp. 71–78. Springer, Berlin (2003)

  58. Histace, A., Meziou, L., Matuszewski, B., Precioso, F., Murphy, M., Carreiras, F.: Statistical region based active contour using a fractional entropy descriptor: application to nuclei cell segmentation in confocal microscopy images. Ann. Br. Mach. Vis. Assoc. 2013(5), 1–15 (2013)

    Google Scholar 

  59. Hiwada, K., Maki, A., Nakashima, A.: Mimicking video: real-time morphable 3D model fitting. In: Proceedings of the ACM symposium on Virtual reality software and technology, pp. 132–139. ACM (2003)

  60. Hodge, A., Fenster, A., Downey, D., Ladak, H.: Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D. Comput. Methods Programs Biomed. 84(2–3), 99–113 (2006)

    Article  Google Scholar 

  61. Hou, Y., Fan, P., Ravyse, I., Enescu, V., Sahli, H.: Smooth adaptive fitting of 3D face model for the estimation of rigid and nonrigid facial motion in video sequences. Signal Process. Image Commun. 26(8), 550–566 (2011)

    Article  Google Scholar 

  62. Hrault, R.: Vision et apprentissage statistique pour la reconnaissance d’items. Ph.D. thesis, Universit de Technologie de Compigne (2007)

  63. Hsu, R.: Face detection and modeling for recognition. Tech. rep, DTIC Document (2002)

  64. Hu, G., Chan, C.H., Yan, F., Christmas, W., Kittler, J.: Robust face recognition by an albedo based 3D morphable model. In: IEEE International Joint Conference on Biometrics (IJCB), pp. 1–8 (2014)

  65. Huber, P.: 4D face: Real-time 3D face tracking and reconstruction from 2D video. https://github.com/patrikhuber/4dface

  66. Huber, P.: eos: A lightweight header-only 3D morphable face model fitting library in modern c++11/14. https://github.com/patrikhuber/eos

  67. Huber, P., Feng, Z.H., Christmas, W., Kittler, J., Rätsch, M.: Fitting 3D morphable models using local features. In: IEEE International Conference on Image Processing (ICIP), pp. 1195–1199 (2015)

  68. Huber, P., Hu, G., Tena, R., Mortazavian, P., Koppen, W., Christmas, W., Rätsch, M., Kittler, J.: A multi resolution 3D morphable face model and fitting framework. In: International Conference on Computer Vision Theory and Applications (VISAPP), pp. 1–8 (2016)

  69. Image, University, V.C.G.B.: Active blobs implementation. http://www.cs.bu.edu/fac/sclaroff/ivc/ActiveBlobs/Home.html

  70. Jolliffe, I.: Principal component analysis. Wiley, New York (2005)

  71. Joshi, P., Tien, W., Desbrun, M., Pighin, F.: Learning controls for blend shape based realistic facial animation. In: ACM SIGGRAPH 2005 Courses, p. 8. ACM (2005)

  72. Kahraman, F., Stegmann, M.: Towards illumination-invariant localization of faces using active appearance models. In: Signal Processing Symposium. NORSIG 2006. IEEE Proceedings of the 7th Nordic, pp. 102–105 (2006)

  73. Kalra, P.: An interactive multimodal facial animation system. Ph.D. thesis, Ecole Polytechnique Fdrale de Lausanne, Switzerland (1993)

  74. Kalra, P., Mangili, A., Thalmann, N., Thalmann, D.: Simulation of facial muscle actions based on rational free form deformations. Comput. Graph. Forum 11(3), 59–69 (1992)

    Article  Google Scholar 

  75. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1(4), 321–331 (1988)

    Article  MATH  Google Scholar 

  76. Kazemi, V., Sullivan, J.: Face alignment with part-based modeling. In: Proceedings of the British Machine Vision Conference, pp. 27–1. BMVA Press (2011)

  77. Kemelmacher-Shlizerman, I.: Internet based morphable model. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3256–3263 (2013)

  78. Kroon, D.J.: Cootes 2D/3D active shape and appearance model for automatic image object segmentation and recognition. http://www.mathworks.com/matlabcentral/fileexchange/

  79. Kuo, P., Hillman, P., Hannah, J.: Improved facial feature extraction for model-based multimedia. In: Proceedings 2nd IEE European Conference on Visual Media Production, pp. 137–146. Citeseer (2005)

  80. La Cascia, M., Isidoro, J., Sclaroff, S.: Head tracking via robust registration in texture map images. In: Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on, pp. 508–514 (1998)

  81. Langs, G., Peloschek, P., Donner, R., Bischof, H.: A clique of active appearance models by minimum description length. In: British Machine Vision Conference (BMCV’05), pp. 859–868 (2005)

  82. Leo, M.J., Manimegalai, D.: 3D modeling of human faces-a survey. In: IEEE 3rd International Conference on Trendz in Information Sciences and Computing (TISC), pp. 40–45 (2011)

  83. Li, Y., Ito, W.: Shape parameter optimization for adaboosted active shape model. In: Tenth IEEE International Conference on Computer Vision. ICCV 2005, vol. 1, pp. 251–258 (2005)

  84. Lima, W.: Face recognition using 3D structural geometry of rigid features extracted from 2D images. Master’s thesis, Universidade do Minho, Escola de Engenharia (2010)

  85. Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: International Joint Conference on Artificial Intelligence, pp. 674–679 (1981)

  86. Magnenat-Thalmann, N., Thalmann, D.: Handbook of virtual humans. Wiley, New York (2005)

  87. Malciu, M., Preteux, F.: Tracking facial features in video sequences using a deformable-model-based approach. In: International Symposium on Optical Science and Technology, pp. 51–62. International Society for Optics and Photonics (2000)

  88. Marshall, D., Cosker, D., Rosin, P., Hicks, Y.: Speech and expression driven animation of a video-realistic appearance based hierarchical facial model. In: Workshop in conjunction with IEEE CVPR of Learning, Representation and Context for Human Sensing in Video. Citeseer (2006)

  89. Martins, P., Caseiro, R., Batista, J.: Non-parametric bayesian constrained local models. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1797–1804 (2014)

  90. Martins, P., Caseiro, R., Henriques, J.F., Batista, J.: Likelihood-enhanced bayesian constrained local models. In: 2014 IEEE International Conference on Image Processing (ICIP), pp. 303–307 (2014)

  91. Martins, P., Henriques, J.F., Caseiro, R., Batista, J.: Bayesian constrained local models revisited. IEEE Trans. Pattern Anal. Mach. Intell. 38(4), 704–716 (2016)

    Article  Google Scholar 

  92. Matthews, I., Baker, S.: Active appearance models revisited. Int. J. Comput. Vis. 60(2), 135–164 (2004)

    Article  Google Scholar 

  93. Maurel, P., McGonigal, A., Keriven, R., Chauvel, P.: 3D model fitting for facial expression analysis under uncontrolled imaging conditions. In: 19th International Conference on Pattern Recognition. ICPR 2008, pp. 1–4 (2008)

  94. Maurer, T., Von der Malsburg, C.: Tracking and learning graphs and pose on image sequences of faces. In: Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp. 176–181 (1996)

  95. Mayer, C., Radig, B.: Learning displacement experts from multi-band images for face model fitting. In: ACHI 2011, The Fourth International Conference on Advances in Computer-Human Interactions, pp. 106–111 (2011)

  96. Menet, S., Saint-Marc, P., Medioni, G.: Active contour models: overview, implementation and applications. In: IEEE International Conference on Systems, Man and Cybernetics, 1990, Conference Proceedings, pp. 194–199 (1990)

  97. Meyer, M., Anderson, J.: Key point subspace acceleration and soft caching. ACM Trans. Graph. (TOG) 26(3), 74 (2007)

    Article  Google Scholar 

  98. Microsoft: face tracking using kinect. https://msdn.microsoft.com/en-us/library/jj130970

  99. Milborrow, S., Nicolls, F.: Locating facial features with an extended active shape model. In: Computer Vision–ECCV 2008, pp. 504–513. Springer, Berlin (2008)

  100. Muré, M.: 3D morphable model software. https://github.com/MichaelMure/3DMM

  101. Nelder, J., Mead, R.: A simplex method for function minimization. Comput. J. 7, 308–313 (1964)

    Article  MathSciNet  MATH  Google Scholar 

  102. Nelder, J., Mead, R.: A simplex method for function minimization. Comput. J. 7(4), 308–313 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  103. Noh, J.Y., Neumann, U.: A survey of facial modeling and animation techniques. Tech. rep., USC Technical Report, pp. 99–705 (1998)

  104. Orozco, J.: Face detection and tracking for facial expression analysis. Ph.D. thesis, Universitat Autónoma de Barcelona (2007)

  105. Pandzic, I.S., Forchheimer, R.: MPEG-4 facial animation: the standard. Implementation and applications. Wiley, New York (2003)

    Google Scholar 

  106. Papandreou, G., Maragos, P.: Adaptive and constrained algorithms for inverse compositional active appearance model fitting. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8 (2008)

  107. Paquet, U.: Convexity and bayesian constrained local models. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1193–1199 (2009)

  108. Pardo, X., Carreira, M., Mosquera, A., Cabello, D.: A snake for CT image segmentation integrating region and edge information. Image Vis. Comput. 19(7), 461–475 (2001)

    Article  Google Scholar 

  109. Parke, F.: Parameterized models for facial animation. IEEE Comput. Graph. Appl. 2(9), 61–68 (1982)

    Article  Google Scholar 

  110. Parke, F.I.: A parametric model for human faces. Ph.D. thesis, University of Utah (1974)

  111. Parke, F.I., Waters, K.: Computer facial animation. CRC Press, Boca Raton (2008)

  112. Patel, A., Smith, W.: 3D morphable face models revisited. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1327–1334 (2009)

  113. Patel, N., Zaveri, M.: 3D facial model reconstruction, expressions synthesis and animation using single frontal face image. Signal, Image Video Process. 7(5), 889–897 (2013)

    Article  Google Scholar 

  114. Peyras, J., Bartoli, A., Mercier, H., Dalle, P.: Segmented aams improve person-independent face fitting. In: In BMVC’07-Proceedings of the 18th British Machine Vision Conference. Citeseer (2007)

  115. Pighin, F., Hecker, J., Lischinski, D., Szeliski, R., Salesin, D.: Synthesizing realistic facial expressions from photographs. In: ACM SIGGRAPH 2006 Courses, p. 19. ACM (2006)

  116. Platt, S., Badler, N.: Animating facial expressions. ACM SIGGRAPH Comput. Graph. 15(3), 245–252 (1981)

    Article  Google Scholar 

  117. Radeva, P., Martí, E.: Facial features segmentation by model-based snakes. In: International Conference on Computing Analysis and Image Processing, Prague, pp. 1–5 (1995)

  118. Ravyse, U., Sahli, H.: A biomechanical model for image-based estimation of 3D face deformations. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2008, pp. 1089–1092 (2008)

  119. Rechenberg, I.: Evolutionsstrategie—optimierung technischer systeme nach prinzipien der biologischen evolution. Ph.D. thesis, Berlin Technical University (1971)

  120. Roberts, M., Cootes, T., Adams, J.: Linking sequences of active appearance sub-models via constraints: an application in automated vertebral morphometry. In: 14th British Machine Vision Conference, vol. 1, pp. 349–358 (2003)

  121. Rogers, M., Graham, J.: Robust active shape model search. In: Computer Vision-ECCV 2002, pp. 517–530. Springer, Berlin (2006)

  122. Romdhani, S., Blanz, V., Vetter, T.: Face identification by fitting a 3D morphable model using linear shape and texture error functions. In: European Conference on Computer Vision, pp. 3–19. Springer, Berlin (2002)

  123. Romdhani, S., Vetter, T.: Estimating 3D shape and texture using pixel intensity, edges, specular highlights, texture constraints and a prior. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 2, pp. 986–993 (2005)

  124. Ross, A.: Procrustes analysis. Department of Computer Science and Engineering, University of South Carolina, Tech. rep. (2004)

  125. Rydfalk, M.: Candide, a parameterized face. Tech. rep., Report No LiTH-ISY-I-866, Dept. of Electrical Engineering, Linkoping University, Sweden (1987)

  126. Salam, H., Seguier, R., Stoiber, N.: Integrating head pose to a 3D multi-texture approach for gaze detection. Int. J. Multimed. Appl. 5(4), 1 (2013)

    Google Scholar 

  127. Salam, H., Stoiber, N., Séguier, R.: A multi-texture approach for estimating iris positions in the eye using 2.5 D active appearance models. In: 2012 19th IEEE International Conference on Image Processing, pp. 1833–1836 (2012)

  128. Saragih, J., Goecke, R.: A nonlinear discriminative approach to aam fitting. In: IEEE 11th International Conference on Computer Vision, 2007, ICCV, pp. 1–8 (2007)

  129. Saragih, J., Lucey, S., Cohn, J.: Deformable model fitting by regularized landmark mean-shift. Int. J. Comput. Vis. 91(2), 200–215 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  130. Sattar, A., Aidarous, Y., Le Gallou, S., Seguier, R.: Face alignment by 2.5D active appearance model optimized by simplex. In: International Conference on Computer Vision Systems (ICVS), pp. 1–10 (2007)

  131. Sattar, A., Aidarous, Y., Seguier, R.: Gagm-aam: a genetic optimization with gaussian mixtures for active appearance models. In: IEEE International Conference on Image Processing (ICIP’08), pp. 3220–3223 (2008)

  132. Sattar, A., Seguier, R.: Facial feature extraction using hybrid genetic-simplex optimization in multi-objective active appearance model. In: IEEE Fifth International Conference on Digital Information Management (ICDIM), pp. 152–158 (2010)

  133. Sclaroff, S., Isidoro, J.: Active blobs. In: Sixth International Conference on Computer Vision, pp. 1146–1153 (1998)

  134. Sederberg, T.W., Scott, P.R.: Free-form deformation of solid geometric models. ACM SIGGRAPH Comput. Graph. 20(4), 151–160 (1986)

    Article  Google Scholar 

  135. Senechal, T., Rapp, V., Salam, H., Seguier, R., Bailly, K., Prevost, L.: Combining aam coefficients with lgbp histograms in the multi-kernel svm framework to detect facial action units. In: IEEE International Conference on Automatic Face and Gesture Recognition and Workshops (FG 2011), pp. 860–865 (2011)

  136. Senechal, T., Rapp, V., Salam, H., Seguier, R., Bailly, K., Prevost, L.: Facial action recognition combining heterogeneous features via multikernel learning. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 42(4), 993–1005 (2012)

  137. Sguier, R., Le Gallou, S., Breton, G., Garcia, C.: Adapted active appearance models. EURASIP J. Image Video Process. 2009(10) (2009)

  138. Shin, H., Lee, Y.: Expression synthesis and transfer in parameter spaces. Comput. Graph. Forum 28(7), 1829–1835 (2009)

    Article  Google Scholar 

  139. Soladié, C., Salam, H., Pelachaud, C., Stoiber, N., Séguier, R.: A multimodal fuzzy inference system using a continuous facial expression representation for emotion detection. In: Proceedings of the 14th ACM international conference on Multimodal interaction, pp. 493–500 (2012)

  140. Stegmann, M.B.: Aam-api. a c++ implementation of the active appearance model framework. http://www.imm.dtu.dk/~aam/

  141. Stoiber, N.: Modeling emotional facial expressions and their dynamics for realistic interactive facial animation on virtual characters. Ph.D. thesis, Universit de Rennes1 (2010)

  142. Storer, M., Urschler, M., Bischof, H.: 3D-mam: 3D morphable appearance model for efficient fine head pose estimation from still images. In: IEEE 12th International Conference on Computer Vision Workshops (ICCV Workshops), pp. 192–199 (2009)

  143. Stricker, R., Martin, C., Gross, H.: Increasing the robustness of 2D active appearance models for real-world applications. In: International Conference on Computer Vision Systems, pp. 364–373. Springer, Berlin (2009)

  144. Su, Y., Gao, X., Tao, D., Li, X.: Gabor-based texture representation in aams. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 2236–2240 (2008)

  145. Sung, J., Kanade, T., Kim, D.: A unified gradient-based approach for combining asm into aam. Int. J. Comput. Vis. 75(2), 297–309 (2007)

    Article  Google Scholar 

  146. Sung, J., Kim, D.: A background robust active appearance model using active contour technique. Pattern recognit. 40(1), 108–120 (2007)

    Article  MATH  Google Scholar 

  147. Tao, H., Huang, T.: Explanation-based facial motion tracking using a piecewise bezier volume deformation model. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–7 (1999)

  148. Terzopoulos, D., Waters, K.: Physically-based facial modelling, analysis, and animation. J. Vis. Comput. Animat. 1(2), 73–80 (1990)

    Article  Google Scholar 

  149. Tian, Y., Kanade, T., Cohn, J.F.: Facial expression recognition. In: Handbook of Face Recognition, pp. 487–519. Springer, Berlin (2011)

  150. Tresadern, P., Bhaskar, H., Adeshina, S., Taylor, C., Cootes, T.: Combining local and global shape models for deformable object matching. In: Proc. British Machine Vision Conference, pp. 1–12 (2009)

  151. Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)

    Article  Google Scholar 

  152. Tzimiropoulos, G.: Active appearance models (aams). a fast but exact version of the simultaneous inverse compositional algorithm (sic). http://www.mathworks.com/matlabcentral/fileexchange/44651-active-appearance-models--aams-

  153. Tzimiropoulos, G., Alabort-i Medina, J., Zafeiriou, S., Pantic, M.: Generic active appearance models revisited. In: Computer Vision—ACCV 2012, pp. 650–663. Springer, Berlin (2012)

  154. Tzimiropoulos, G., Pantic, M.: Optimization problems for fast aam fitting in-the-wild. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 593–600 (2013)

  155. Van Ginneken, B., Frangi, A.F., Staal, J.J., Romeny, B.M., Viergever, M.A.: Active shape model segmentation with optimal features. IEEE Transactions on medical Imaging21(8), 924–933 (2002)

  156. Viola, P., Jones, M.J., Snow, D.: Detecting pedestrians using patterns of motion and appearance. Int. J. Comput. Vis. 63(2), 153–161 (2005)

    Article  Google Scholar 

  157. Wang, Y., Lucey, S., Cohn, J.F.: Enforcing convexity for improved alignment with constrained local models. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 1–8 (2008)

  158. Waters, K.: A muscle model for animation three-dimensional facial expression. ACM SIGGRAPH Comput. Graph. 21(4), 17–24 (1987)

    Article  Google Scholar 

  159. Weissenfeld, A., Urfalioglu, O., Liu, K., Ostermann, J.: Robust rigid head motion estimation based on differential evolution. In: IEEE International Conference on Multimedia and Expo, pp. 225–228 (2006)

  160. Wen, Z., Huang, T.S.: 3D face processing, modeling, analysis and synthesis. Kluwer academic publishers, Dordrecht (2004)

  161. Wen, Z., Huang, T.S.: 3D Face Processing: modeling, analysis and synthesis, vol. 8. Springer, Berlin (2006)

  162. Whitmarsh, T., Veltkamp, R., Spagnuolo, M., Marini, S., ter Haar, F.: Landmark detection on 3D face scans by facial model registration. In: 1st international symposium on shapes and semantics, pp. 71–75 (2006)

  163. Wiskott, L., Fellous, J., Kuiger, N., Von der Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 775–779 (1997)

    Article  Google Scholar 

  164. Wu, Y., Liu, H., Zha, H.: A new method of detecting human eyelids based on deformable templates. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp. 604–609 (2004)

  165. Xiao, J., Baker, S., Matthews, I., Kanade, T.: Real-time combined 2D+3D active appearance models. In: Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition, pp. 535–542 (2004)

  166. Xin, W., Yunxia, T.: A faster b spline snake. In: IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 2314–2319 (2009)

  167. Xu, Z., Chen, H., Zhu, S., Luo, J.: A hierarchical compositional model for face representation and sketching. IEEE Trans. Pattern Anal. Mach. Intell. 30(6), 955–969 (2008)

    Article  Google Scholar 

  168. Yan, P., Xu, S., Turkbey, B., Kruecker, J.: Discrete deformable model guided by partial active shape model for trus image segmentation. IEEE Trans Biomed. Eng. 57(5), 1158–1166 (2010)

    Article  Google Scholar 

  169. Yan, X.: Constrained local model (clm) implementation. https://sites.google.com/site/xgyanhome/home/projects/clm-implementation

  170. Yang, Y., Ramanan, D.: Articulated pose estimation with flexible mixtures-of-parts. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1385–1392 (2011)

  171. Ybanez Zepeda, J.: A linear estimation of the face’s tridimensional pose and facial expressions. Ph.D. thesis, Telecom ParisTech (2007)

  172. Yongxin, G., Dan, Y., Jiwen, L., Bo, L., Xiaohong, Z.: Active appearance models using statistical characteristics of gabor based texture representation. J. Vis. Commun. Image Represent. 24(5), 627–634 (2013)

    Article  Google Scholar 

  173. Yu, M., Tiddeman, B.P.: Facial feature detection and tracking with a 3d constrained local model. In: International Conferences in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), pp. 181–188 (2010)

  174. Yuille, A., Hallinan, P.W., Cohen, D.S.: Feature extraction from faces using deformable templates. Int. J. Comput. Vis. 8(2), 99–111 (1992)

    Article  Google Scholar 

  175. Zalewski, L., Gong, S.: 2D statistical models of facial expressions for realistic 3D avatar animation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR, vol. 2, pp. 217–222 (2005)

  176. Zhang, C., Cohen, F.: Component-based active appearance models for face modelling. In: Advances in Biometrics, pp. 206–212. Springer, Berlin (2005)

  177. Zheng, S., Sturgess, P., Torr, P.H.S.: Approximate structured output learning for constrained local models with application to real-time facial feature detection and tracking on low-power devices. In: 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), pp. 1–8 (2013)

  178. Zhou, Y., Gu, L., Zhang, H.: Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference. In: Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. I–109 (2003)

  179. Zhu, X.: Face detection, pose estimation and landmark localization in the wild. https://www.ics.uci.edu/~xzhu/face/

  180. Zhu, X., Ramanan, D.: Face detection, pose estimation and landmark localization in the wild. In: Computer Vision and Pattern Recognition (CVPR), pp. 68–79 (2012)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hanan Salam.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Salam, H., Séguier, R. A survey on face modeling: building a bridge between face analysis and synthesis. Vis Comput 34, 289–319 (2018). https://doi.org/10.1007/s00371-016-1332-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-016-1332-y

Keywords

Navigation