Interactive Feature Visualization and Detection for 3D Face Classification

Authors:
Jason McLaughlin;Shiaofen Fang;Sandra W. Jacobson;H. Eugene Hoyme;Luther Robinson;Tatiana Foroud
Affiliations:
Indiana University-Purdue University, USA;Indiana University-Purdue University, USA;Wayne State University, USA, and University of Cape Town, South Africa;Sanford School of Medicine, USA;State University of New York, USA;Indiana University, USA
Venue:
International Journal of Cognitive Informatics and Natural Intelligence
Year:
2011

Citing 7
Cited 0

Design galleries: a general approach to setting parameters for computer graphics and animation

Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Tracking and Visualizing Turbulent 3D Features

IEEE Transactions on Visualization and Computer Graphics
Curvature-Based Face Surface Recognition Using Spherical Correlation - Principal Directions for Curved Object Recognition

FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Iconic Techniques for Feature Visualization

VIS '95 Proceedings of the 6th conference on Visualization '95
Using Facial Images to Diagnose Fetal Alcohol Syndrome (FAS)

ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Hardware-Assisted Feature Analysis and Visualization of Procedurally Encoded Multifield Volumetric Data

IEEE Computer Graphics and Applications
Simplified Gaussian and Mean Curvatures to Range Image Segmentation

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new visual approach to the surface shape analysis and classification of 3D facial images is presented. It allows the users to visually explore the natural patterns and geometric features of 3D facial scans to provide decision-making information for face classification which can be used for the diagnosis of diseases that exhibit facial characteristics. Using surface feature analysis under a digital geometry analysis framework, the method employs an interactive feature visualization technique that allows interactive definition, modification and exploration of facial features to provide the best discriminatory power for a given classification problem. OpenGL based surface shading and interactive lighting are employed to generate visual maps of discriminatory features to visually represent the salient differences between labeled classes. This technique will be applied to a medical diagnosis application for Fetal Alcohol Syndrome FAS which is known to exhibit certain facial patterns.