Shape from shading
Linear Object Classes and Image Synthesis From a Single Example Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Multilinear Analysis of Image Ensembles: TensorFaces
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Facial Expression Decomposition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Simple Coupled Statistical Model for 3D Face Shape Recovery
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Algorithm 862: MATLAB tensor classes for fast algorithm prototyping
ACM Transactions on Mathematical Software (TOMS)
The Appearance of Human Skin: A Survey
Foundations and Trends® in Computer Graphics and Vision
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Facial Image Manipulation System and Facial Texture Analysis
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 06
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Facial pose synthesis is applied to generate much required information for several applications, such as public security, facial cosmetology, etc. How to synthesize facial pose images from one image accurately without spatial information is still a challenging problem. In this paper we propose a tensor-based subspace learning method (TSL) for synthesizing human multi-pose facial images from a single two-dimensional image. In the proposed TSL method, two-dimensional multi-pose images in the database are previously organized into a tensor form and a tensor decomposition technique is applied to build projection subspaces. In synthesis processing, the input two-dimensional image is first projected into its corresponding projection subspace to get an identity vector and then the identity vector is used to generate other novel pose images. Our technique is applied on KAO-Ritsumeikan Multi-angle View, Illumination and Cosmetic Facial Database (MaVIC) and experiment results show the effectiveness of our proposed method for facial pose synthesis.