Abstract
In aging simulation, the most essential requirements are (1) human identity should remain stable in texture synthesis; and (2) the texture synthesized is expected to accord with human cognitive perception in aging. In this paper, we address the problem of face aging simulation by using a tensor completion based method. The proposed method is composed of two steps. In the first stage, Active Appearance Models (AAM) is applied to facial images to normalize pose variations. In the second stage, the tensor completion based aging simulation method is adopted to synthesize aging effects on facial images. By introducing age and identity prior information in the tensor space, human identity is mostly protected during the aging procedure and proper textures are generated to simulate the aged appearance. Experimental results achieved on the FG-NET database are not only in the age as subjective expectation, but also reserve the person specific cues, which demonstrates the effectiveness of the proposed method.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Fu, Y., Guo, G., Huang, T.S.: Age Synthesis and Estimation via Faces: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(11), 1955–1976 (2010)
Ramanathan, N., Chellappa, R., Biswas, S.: Computational Methods for Modeling Facial Aging: A Survey. Journal of Visual Languages & Computing 20(3), 131–144 (2009)
Lanitis, A., Taylor, C.J., Cootes, T.F.: Modeling the process of aging in face images. In: 7th International Conference on Computer Vision, pp. 131–136. IEEE Press, Kerkyra (1999)
Lanitis, A., Taylor, C.J., Cootes, T.F.: Toward Automatic Simulation of Aging Effects on Face Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(2), 442–455 (2002)
Ramanathan, N., Chellappa, R.: Modeling age progression in young faces. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 387–394. IEEE Press, New York (2006)
Ramanathan, N., Chellappa, R.: Modeling shape and textural variations in aging faces. In: 8th IEEE International Conference on Automatic Face & Gesture Recognition, pp. 1–8. IEEE Press, Amsterdam (2008)
Perez, P., Gangnet, M., Blake, A.: Poisson Image Editing. ACM Transaction on Graphics 22(3), 313–318 (2002)
Park, U., Tong, Y., Jain, A.K.: Age-Invariant Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(5), 947–954 (2010)
Suo, J., Min, F., Zhou, S., Shan, S., Chen, X.: A multi-resolution dynamic model for face aging simulation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press, Minneapolis (2007)
Suo, J., Zhu, S., Shan, S., Chen, X.: A Compositional and Dynamic Model for Face Aging. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(3), 385–401 (2010)
Wang, Y., Zhang, Z., Li, W., Jiang, F.: Combining Tensor Space Analysis and Active Appearance Models for Aging Effect Simulation on Face Images. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 42(4), 1107–1118 (2012)
Vasilescu, M.A.O., Terzopoulos, D.: Multilinear analysis of image ensembles: tensorfaces. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part I. LNCS, vol. 2350, pp. 447–460. Springer, Heidelberg (2002)
Chen, Y., Hsu, C., Liao, H.Y.M.: Simultaneous Tensor Decomposition and Completion using Factor Priors. IEEE Transactions on Pattern Analysis and Machine Intelligence 36(3), 577–591 (2014)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active Appearance Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 681–685 (2001)
Liu, J., Musialski, P., Wonka, P., Ye, J.: Tensor Completion for Estimating Missing Values in Visual Data. IEEE Transactions on Pattern Analysis and Machine Intelligence 35(1), 208–220 (2013)
Liu, J., Musialski, P., Wonka, P., Ye, J.: Tensor completion for estimating missing values in visual data. In: 12th International Conference on Computer Vision, pp. 2114–2121. IEEE Press, Kyoto (2009)
Wang, H., Ahuja, N.: Facial expression decomposition. In: 9th International Conference on Computer Vision, pp. 958–965. IEEE Press, Nice (2003)
Chen, Y., Hsu, C.: Multilinear Graph Embedding: Representation and Regularization for Images. IEEE Transactions on Image Processing 23(2), 741–754 (2014)
Lin, Z., Chen, M., Wu, L., Ma, Y.: The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices. Technical Report UILU-ENG-09-2215, Univ. of Illinois at Urbana-Champaign (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, H., Huang, D., Wang, Y., Yang, H. (2015). Facial Aging Simulation via Tensor Completion. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_83
Download citation
DOI: https://doi.org/10.1007/978-3-319-25417-3_83
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25416-6
Online ISBN: 978-3-319-25417-3
eBook Packages: Computer ScienceComputer Science (R0)