Title :
Human Face Feature Extraction and Recognition Base on SIFT
Author :
Yanbin, Han ; Jianqin, Yin ; Jinping, Li
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
Abstract :
An important algorithm SIFT, which has been successfully applied in image matching, is employed in face recognition. Firstly, the main region of a face is detected from background images by AdaBoost. Secondly, face features are extracted by using SIFT. Then, face recognition is conducted by the comparing real extracted features with training sets. Experiment shows that, in the ORAL face DB, this scheme can reserve the advantages of SIFT, and have a high robustness in face description.
Keywords :
face recognition; feature extraction; image matching; message authentication; transforms; AdaBoost; ORAL face DB; SIFT; human face feature extraction; human face recognition; image matching; scale invariant feature transform; Convolution; Face detection; Face recognition; Feature extraction; Humans; Image databases; Image matching; Image recognition; Principal component analysis; Robustness; AdaBoost; SIFT; face recognition; image match;
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
DOI :
10.1109/ISCSCT.2008.249
