Ellipsoidal face model-based image registration for generating facial textures

Authors:
Seok-Woo Jang;Myung-Ae Chung;Gye-Young Kim
Affiliations:
Anyang University, Anyang-Dong, Manan-Gu, Anyang, Korea;ETRI, Gajeong-Ro, Yuseong-Gu, Daejeon, Korea;Soongsil Universtiy, Sangdo Dong, Dongjak-Gu, Seoul, Korea
Venue:
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Year:
2012

Citing 7
Cited 0

A Feature-Based, Robust, Hierarchical Algorithm for Registering Pairs of Images of the Curved Human Retina

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Image Registration Algorithm Based on Cylindrical Prototype Model

ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Real Time 3D Face Pose Tracking From an Uncalibrated Camera

CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
The Asymmetry of Image Registration and Its Application to Face Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence
2D face recognition based on supervised subspace learning from 3D models

Pattern Recognition
Region-based image registration for mosaicking

International Journal of Computer Applications in Technology
Reinterpreting the Application of Gabor Filters as a Manipulation of the Margin in Linear Support Vector Machines

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose an ellipsoidal face model-based image registration method to generate realistic facial textures. The suggested algorithm registers multiple 2D face images captured in different views with size-variable block matching that reflects both left-and-right and up-and-down face curvatures. For accurate block matching, the algorithm simultaneously considers color and texture features. It then employs weighting factor-based mosaiking and ghosting artifact elimination techniques to generate natural facial textures from registered images. Experimental results are given to demonstrate that the suggested ellipsoidal face model-based image registration algorithm can perform more effectively than other conventional approaches.