Original Research Article
Article volume = 2021 and issue = 2
Article publication Date: November, 1, 2021
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Apply Tensorial Methods for Detecting and Recovering Facial Shapes
Ali Reza Shojaeifard(a), Hamid Reza Yazdani(b), Mohsen Shahrezaee(c)
(a)Imam Hossein Comprehensive University, Department of Mathematics and Statistics Tehran, Iran.
(b)Imam Hossein Comprehensive University, Department of Mathematics and Statistics Tehran, Iran.
(c)Imam Hossein Comprehensive University, Faculty of Defense and Engineering, Tehran, Iran.
This paper proposes a fast 3-D facial shape recovery algorithm from a single image with general, Unknown lighting. To derive the algorithm, we formulate a non-linear least-square problem with two-parameter vectors which are related to personal identity and light conditions. We then Combine the spherical harmonics for the surface normal of a human face with tensor algebra and show that in a certain condition, the dimensionality of the least-square problem can be further reduced to one-tenth of the regular subspace-based model by using tensor decomposition (N-mode SVD), which speeds up the computations. To enhance the shape recovery performance, we have incorporated prior information in updating the parameters. The proposed algorithm takes less than 0.4 s to reconstruct a face in the experiment and shows a significant performance improvement over other reported scheme.
Facial shape recovery, Image processing, Statistical face model, Tensorial methods.
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Cite this article as:
- Ali Reza Shojaeifard, Hamid Reza Yazdani, Mohsen Shahrezaee, Apply Tensorial Methods for Detecting and Recovering Facial Shapes, Communications in Combinatorics, Cryptography & Computer Science, 2021(2), PP.129–135, 2021
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