DocumentCode :
1739657
Title :
Eigenspace-based human face detection
Author :
Rujie, Liu ; Baozong, Yuan
Author_Institution :
Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
1305
Abstract :
An eigenspace based human face detection method is proposed. The distribution of human face patterns in image space is modeled by means of the Mahalanobis-based clustering method. The eigenspace decomposition approach for conditional probability density estimation includes both the distance measure between the sample and eigenspace and the measure of sample projection and cluster centroid which is more robust than the traditional probability density estimation method where only the latter distance is considered. Thus it can achieve better human face detection result
Keywords :
Gaussian processes; eigenvalues and eigenfunctions; face recognition; image sampling; object detection; parameter estimation; pattern clustering; probability; Gaussian density estimation; Mahalanobis-based clustering method; cluster centroid; conditional probability density estimation; distance measure; eigenspace based human face detection method; eigenspace decomposition; eigenspace-based human face detection; face recognition; human face patterns distribution; image space; sample projection; Clustering methods; Covariance matrix; Density measurement; Face detection; Face recognition; Gaussian distribution; Humans; Information science; Multidimensional systems; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
Type :
conf
DOI :
10.1109/ICOSP.2000.891785
Filename :
891785
Link To Document :
بازگشت