Title :
New Method for Locating the 3D Facial Landmark Points
Author :
Zhang, Yongze ; Da, Feipeng ; Li, Xiaoli ; Gai, Shaoyan
Author_Institution :
Res. Inst. of Autom., Southeast Univ., Nanjing, China
Abstract :
Locating landmark points plays an important role in applications related to human faces, such as registration of 3D faces, the deformation based on the fiducial points, and so on. We present a new form of three-dimensional shape representation based on the local projecting area, and suggest an algorithm of locating the landmark points with it. This representation is invariant to rotation and translation, and need no training of gallery face set. Comparing with the classical method such as that using shape index, it doesn´t require complex curvature computation of point cloud, without demand of large local neighborhood and the high quality of point cloud. So the proposed algorithm has lower amount of computation and better veracity.
Keywords :
computational geometry; face recognition; image reconstruction; image registration; image representation; shape recognition; 3D face deformation; 3D face registration; 3D facial landmark point location algorithm; complex curvature computation; fiducial point; gallery face set training; geometrical rotation; geometrical translation; local projection area; point cloud quality; shape index; three-dimensional shape representation; Automation; Cloud computing; Face; Humans; Iterative closest point algorithm; Principal component analysis; Shape;
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
DOI :
10.1109/CCPR.2009.5344120