Title :
A hybrid technique for facial feature point detection
Author :
Gargesha, M. ; Panchanathan, S.
Author_Institution :
Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA
Abstract :
Existing techniques for facial feature point detection from color images include template matching, facial geometry and symmetry analysis, mathematical morphology, luminance and chrominance analysis, and PCA. However, these techniques are plagued by poor performance in the presence of scale variations. In this paper, a hybrid technique is proposed that employs a combination of the above approaches along with curvature analysis of the intensity surface of the face image in order to provide a superior performance with reduced computational complexity, even in the presence of scale variations
Keywords :
face recognition; feature extraction; image colour analysis; image matching; mathematical morphology; principal component analysis; PCA; chrominance analysis; color images; computational complexity reduction; curvature analysis; face image; facial feature point detection; facial geometry; hybrid technique; intensity surface; luminance analysis; mathematical morphology; performance; symmetry analysis; template matching; Computational complexity; Eyes; Face detection; Facial features; Image analysis; Image color analysis; Image edge detection; Nose; Performance analysis; Principal component analysis;
Conference_Titel :
Image Analysis and Interpretation, 2002. Proceedings. Fifth IEEE Southwest Symposium on
Conference_Location :
Sante Fe, NM
Print_ISBN :
0-7695-1537-1
DOI :
10.1109/IAI.2002.999905