Abstract
In this paper, we propose a novel and efficient algorithm to reconstruct the 3D structure of a human face from one or a number of its 2D images with different poses. In our proposed algorithm, the rotation and translation process from a frontal-view face image to a non-frontal-view face image is at first formulated as a constrained independent component analysis (cICA) model. Then, the overcomplete ICA problem is converted into a normal ICA problem. The CANDIDE model is also employed to design a reference signal in our algorithm. Moreover, a model-integration method is proposed to improve the depth-estimation accuracy when multiple non-frontal-view face images are available. Experimental results on a real 3D face image database demonstrate the feasibility and efficiency of the proposed method.
This work was supported by a grant from the RGC of the HKSAR, China (Project No. PolyU 5207/O8E) and a grant from National Science Foundation of China (No. 60905023).
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References
Ahlberg, J.: CANDIDE-3 – updated parameterised face. Linkoping University, Lysator LiTH-ISY-R-2325 (2001)
Bregler, C., Hertzmann, A., Biermann, H.: Recovering non-rigid 3D shape from image streams. In: Proc. IEEE Comput. Soc. Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 690–696 (2000)
Cootes, T., Taylor, C.: A mixture model for representing shape variation. In: Clark, A.F. (ed.) Proceedings of the 8th British Machine Vision Conference, vol. 1, pp. 110–119. Britich Machine Vision Association Press (1997)
Fanany, M.I., Kumazawa, I.: A neural network for recovering 3D shape from erroneous and few depth maps of shaded images. Pattern Recognition Letters 25(4), 377–389 (2004)
Huang, D.S., Min, J.X.: A new constrained independent component analysis method. IEEE Transaction Neural Networks 18(5), 1532–1535 (2007)
Lu, W., Rajapakse, J.C.: Approach and applications of constrained ICA. IEEE Transaction Neural Networks 16(1), 203–212 (2005)
Lu, W., Rajapakse, J.C.: ICA with reference. Neurocomputing 69, 2244–2257 (2006)
Romdhani, S., Vetter, T.: Efficient, robust and accurate fitting of a 3D morphable model. In: IEEE International Conference on Computer Vision, vol. 2(1), pp. 59–66 (2003)
Savran, A., Alyüz, N., Dibeklioğlu, H., Çeliktutan, O., Gökberk, B., Sankur, B., Akarun, L.: Bosphorus database for 3D face analysis. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds.) BIOID 2008. LNCS, vol. 5372, pp. 47–56. Springer, Heidelberg (2008)
Sun, Z.L.: An extension of MISEP for post-nonlinear-linear mixture separation. IEEE Transactions on Circuits and Systems Part II: Express Briefs 56(8), 654–658 (2009)
Sun, Z.L., Huang, D.S., Zheng, C.H., Shang, L.: Optimal selection of time lags for TDSEP based on genetic algorithm. Neurocomputing 69(7-9), 884–887 (2006)
Sun, Z.L., Shang, L.: An improved constrained ICA with reference based unmixing matrix initialization. Neurocomputing 73(4-6), 1013–1017 (2010)
Torresani, L., Hertzmann, A., Bregler, C.: Learning non-rigid 3D shape from 2D motion. In: Advances in Neural Information Processing Systems. MIT Press, Cambridge (2003)
Zhang, C.Z., Cohen, F.S.: 3-D face structure extraction and recognition from images using 3-D morphing and distance mapping. IEEE Transactions on Image Processing 11(1), 1249–1259 (2002)
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Sun, ZL., Lam, KM. (2010). Depth Estimation of Face Images Based on the Constrained ICA Model. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_48
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DOI: https://doi.org/10.1007/978-3-642-15702-8_48
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