Video-based facial expression hallucination: a two- level hierarchical fusion approach

Authors:
Jian Zhang;Yueting Zhuang;Fei Wu
Affiliations:
College of Computer Science & Technology, Zhejiang University, Hangzhou, P.R. China;College of Computer Science & Technology, Zhejiang University, Hangzhou, P.R. China;College of Computer Science & Technology, Zhejiang University, Hangzhou, P.R. China
Venue:
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Year:
2006

Citing 9
Cited 1

The FERET Evaluation Methodology for Face-Recognition Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Expressive expression mapping with ratio images

Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Hallucinating Faces

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Geometry-driven photorealistic facial expression synthesis

Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Facial Expression Hallucination

WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
An Improved Two-Step Approach to Hallucinating Faces

ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Eigenfaces for recognition

Journal of Cognitive Neuroscience
Hallucinating face by eigentransformation

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

Hallucinating faces: LPH super-resolution and neighbor reconstruction for residue compensation

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Facial expression hallucination is an important approach to facial expression synthesis. Existing works mainly focused on synthesizing a static facial expression image given one face image with neutral expression. In this paper, we propose a novel two-level hierarchical fusion approach to hallucinate dynamic expression video sequences when given only one neutral expression face image. By fusion of local linear and global nonlinear subspace learning, the two-level approach provides a sound solution to organizing the complex video sample space. Experiments show that our approach generates reasonable facial expression sequences both in temporal domain and spatial domain with less artifact compared with existing works.