TY - GEN
T1 - Interactive feature visualization and detection for 3D face classification
AU - McLaughlin, Jason
AU - Fang, Shiaofen
AU - Huang, Jeffrey
AU - Jacobson, Sandra
AU - Hoyme, H. Eugene
AU - Robinson, Luther
AU - Foroud, Tatiana
PY - 2010
Y1 - 2010
N2 - A new visual approach to the surface shape analysis and classification of 3D facial images is presented. It aims to allow 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, we employ 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.
AB - A new visual approach to the surface shape analysis and classification of 3D facial images is presented. It aims to allow 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, we employ 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.
KW - 3D image analysis
KW - Feature visualization
KW - Medical diagnosis
KW - Pattern classification
KW - Polygon mesh surface
KW - Shading and lighting
UR - https://www.scopus.com/pages/publications/78649805084
U2 - 10.1109/COGINF.2010.5599748
DO - 10.1109/COGINF.2010.5599748
M3 - Conference contribution
AN - SCOPUS:78649805084
SN - 9781424480401
T3 - Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010
SP - 160
EP - 167
BT - Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010
T2 - 9th IEEE International Conference on Cognitive Informatics, ICCI 2010
Y2 - 7 July 2010 through 9 July 2010
ER -