Three Dimensional Posed Face Recognition with an Improved Iterative Closest Point Method-Reference-Cited by-同舟云学术

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Three Dimensional Posed Face Recognition with an Improved Iterative Closest Point Method

Published:2019-07-13 Issue:3-4 Volume:10 Page:
ISSN:2092-6731
Container-title:3D Research
language:en
Short-container-title:3D Res

Author:

Mohammadi Shahram^ORCID,Gervei Omid

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s13319-019-0232-0.pdf

Reference54 articles.

1. Bowyer, K. W., Chang, K., & Flynn, P. (2006). A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Computer Vision and Image Understanding, 101, 1–15.

2. Zhao, W., Chellappa, R., Phillips, P. J., & Rosenfeld, A. (2003). Face recognition: A literature survey. ACM Computing Surveys (CSUR), 35, 399–458.

3. Soltanpour, S., Boufama, B., & Wu, Q. J. (2017). A survey of local feature methods for 3D face recognition. Pattern Recognition, 72, 391–406.

4. Guo, Y., Bennamoun, M., Sohel, F., Lu, M., Wan, J., & Kwok, N. M. (2016). A comprehensive performance evaluation of 3D local feature descriptors. International Journal of Computer Vision, 116, 66–89.

5. Wang, Y., Liu, J., & Tang, X. (2010). Robust 3D face recognition by local shape difference boosting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 1858–1870.

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