The spiral facets: A unified framework for the analysis and description of 3D facial mesh surface

Authors:
Naoufel Werghi;Haykel Boukadida;Youssef Meguebli
Affiliations:
Computer Engineering Departmen, Khalifa University, Khalifa, United Arab Emirates;School of Sciences and Techniques, University of Tunis, Tunis, Tunisia;School of Sciences and Techniques, University of Tunis, Tunis, Tunisia
Venue:
3D Research
Year:
2010

Citing 21
Cited 0

Introduction to algorithms

Introduction to algorithms
Finding Surface Correspondance for Object Recognition and Registration Using Pairwise Geometric Histograms

ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
3D Human Face Recognition Using Point Signature

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
3D Shape-based Face Recognition using Automatically Registered Facial Surfaces

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Deformation Analysis for 3D Face Matching

WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Detection of Anchor Points for 3D Face Veri.cation

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A 3D Facial Expression Database For Facial Behavior Research

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Combining local features for robust nose location in 3D facial data

Pattern Recognition Letters
Description and retrieval of 3D face models using iso-geodesic stripes

MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Integration of local and global geometrical cues for 3D face recognition

Pattern Recognition
Automatic 3D facial segmentation and landmark detection

ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional face recognition using combinations of surface feature map subspace components

Image and Vision Computing
3D Face Recognition by Local Shape Difference Boosting

ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
An Intrinsic Framework for Analysis of Facial Surfaces

International Journal of Computer Vision
Landmark Localisation in 3D Face Data

AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
3-D face detection, landmark localization, and registration using a point distribution model

IEEE Transactions on Multimedia
Expression-invariant 3D face recognition

AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Face authentication based on multiple profiles extracted from range data

AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Automatic 3D face recognition combining global geometric features with local shape variation information

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we describe an original topological framework for encoding 3D facial triangular mesh surface. We derive shape information from the triangular mesh surface by exploiting specific arrangements of facets in the model. We describe the foundations of the framework and show how it can be employed in several original applications including face landmark detection, frontal face extraction, face orientation and facial surface representation. We validate the framework through experimentation with raw 3D face mesh surfaces and demonstrate that the model allows simpler implementation, more compact representation and encompasses rich shape information that can be usefully deployed both locally and globally across the face in comparison to other standard representations.