Abstract

Active Appearance Model (AAM) is one of the most popular techniques that extract features by precise modelling of human faces under various physical and environmental circumstances. In such active appearance model, fitting the model with original image is a challenging task. State of the art shows some of the optimization methods that are applicable to resolve the optimization problem. This encourages us to review the recent improvements of AAM fitting based on optimization methods. This study provides an up-to-date review of researches as regards to AAM optimization; studies are reviewed and discussed in four different sections. This review evidently explores the limitations of the previous works to facilitate better understanding different kind of approaches. The aim of this study is to help as a guide for further studies.

Keywords:

Active appearance model, fitting, face recognition,

References

1. Abdulameer, M.H., S.N.S. Abdullah and Z.A. Othman, 2013. Face recognition technique based on active appearance model. Int. Rev. Comput. Software (IRECOS), 8(11): 2733-2739.
   
2. Abdulameer, M.H., S.N. Sheikh Abdullah and Z.A. Othman, 2014. A modified active appearance model based on an adaptive artificial bee colony. Sci. World J., 2014: 879031.
   CrossRef    PMid:25165748 PMCid:PMC4139015    
3. Andreopoulos, A. and J.K. Tsotsos, 2005. A novel algorithm for fitting 3-D active appearance models: Applications to cardiac MRI segmentation. Proceedings of the 14th Scandinavian conference on Image Analysis (SCIA'05). Joensuu, Finland, pp: 729-739.
   CrossRef    
4. Baek, S.Y., B.Y. Kim and K. Lee, 2009. 3D face model reconstruction from single 2D frontal image. Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry. New York, pp: 95-101.
   CrossRef    
5. Berry, C., A. Kokaram and N. Harte, 2011. An extended multiresolution approach to mouth specific AAM fitting for speech recognition. Proceeding of the 19th European Signal Processing Conference. Barcelona, Spain, pp: 1959-1963.
   
6. Bosch, H.G., S.C. Mitchell, B.P.F. Lelieveldt, F. Nijland, O. Kamp, M. Sonka and J.H. Reiber, 2001. Active appearance motion models for endocardial contour detection in time sequences of echocardiograms. Proceeding of SPIE 4322, Medical Imaging 2001: Image Processing, pp: 257-268.
   
7. Christoudias, C.M., L.P. Morency and T. Darrell, 2004. Light Field Appearance Manifolds. In: Pajdla, T. and J. Matas (Eds.), Computer Vision - ECCV 2004, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Heidelberg, 3024: 481-493.
   CrossRef    
8. Christoudias, C.M., L.P. Morency and T. Darrell, 2006. Non-parametric and light-field deformable models. Comput. Vis. Image Und., 104(1): 16-35.
   CrossRef    
9. Cootes, T.F., G.J. Edwards and C.J. Taylor, 1998. Active appearance models. Proceeding of European Conference on Computer Vision, 2: 484-498.
   CrossRef    
10. Donner, R., M. Reiter, G. Langs, P. Peloschek and H. Bischof, 2006. Fast active appearance model search using canonical correlation analysis. IEEE T. Pattern Anal., 28(10): 1690-1694.
    CrossRef    PMid:16986548    
11. Gao, X., Y. Su, X. Li and D. Tao, 2010. A review of active appearance models. IEEE T. Syst. Man Cy. C, 40(2): 145-158.
    CrossRef    
12. Goodall, C., 1991. Procrustes methods in the statistical analysis of shape. J. Roy. Stat. Soc. B Met., pp: 285-339.
    
13. Huang, X., J. Gao, S.C.S. Cheung and R. Yang, 2010. Manifold estimation in view-based feature space for face synthesis across poses. Proceeding of the 9th Asian Conference on Computer Vision (ACCV'09), pp: 37-47.
    CrossRef    
14. Hu, C., J. Xiao, I. Matthews, S. Baker, J. Cohn and T. Kanade, 2004. Fitting a single active appearance model simultaneously to multiple images. Proceeding of the British Machine Vision Conference, September, pp: 1-10.
    CrossRef    
15. Kawarazaki, Y., G. Duan, T. Shinkawa and Y.W. Chen, 2011. Viewpoint-specific active appearance model for robust feature point extraction. Proceeding of the 6th International Conference on Computer Sciences and Convergence Information Technology (ICCIT, 2011), pp: 883-886.
    PMCid:PMC3148723    
16. Lee, H.S. and D. Kim, 2009. Tensor-based AAM with continuous variation estimation: Application to variation-robust face recognition, IEEE T. Pattern Anal., 31(6): 1102-1116.
    CrossRef    PMid:19372613    
17. Lucey, S., I. Matthews, C. Hu, Z. Ambadar, F. de la Torre and J. Cohn, 2006. AAM derived face representations for robust facial action recognition. Proceeding of the 7th IEEE International Conference on Automatic Face and Gesture Recognition (FGR, 2006), pp: 155-160.
    CrossRef    
18. Matthews, I. and S. Baker, 2004. Active appearance models revisited. Int. J. Comput. Vision, 60(2): 135-164.
    CrossRef    
19. Peyras, J., A. Bartoli, H. Mercier and P. Dalle, 2007. Segmented AAMs improve person-independent face fitting. Proceeding of the 18th British Machine Vision Conference (BMVC'07), pp: 1-10.
    
20. Sethuram, A., K. Ricanek and E. Patterson, 2010. A comparative study of active appearance model annotation schemes for the face. Proceeding of the 7th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP '10), pp: 367-374.
    CrossRef    
21. Sung, J. and D. Kim, 2006. STAAM: Fitting a 2d+3d AAM to stereo images. Proceeding of the International Conference on Image Processing. Atlanta, GA, pp: 2781-2784.
    CrossRef    
22. Sung, J., T. Kanade and D. Kim, 2007. A unified gradient-based approach for combining ASM into AAM. Int. J. Comput. Vision, 75(2): 297-309.
    CrossRef    
23. Sung, J., T. Kanade and D. Kim, 2008. Pose robust face tracking by combining active appearance models and cylinder head models. Int. J. Comput. Vision, 80(2): 260-274.
    CrossRef    
24. Wang, W., S. Shan, W. Gao and B. Yin, 2003. Combining active shape models and active appearance models for accurate image interpretation. ICASSP, pp: 1-4.
    
25. Wang, Y.K. and W.R. Chen, 2010. Facial feature alignment by manifold learning of active appearance model. Proceeding of the 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP, 2010), pp: 224-227.
    CrossRef    
26. Xiao, J., S. Baker, I. Matthews and T. Kanade, 2004. Real-time combined 2d+3d active appearance models. Proceeding of the 2004 IEEE Computer Society Conference on Computer vision and Pattern Recognition (CVPR'04), pp: 535-542.
    
27. Yan, S., C. Liu, S.Z. Li, H. Zhang, H.Y. Shum and Q. Cheng, 2002. Texture-constrained active shape models. Proceeding of the 1st International Workshop Generative-Model-Based Vision, pp: 107-113.
    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.