Paper Info
Title
A real-time face tracker for color video
Abstract
This paper presents a face localization and tracking algorithm which is based upon skin color detection and principal component analysis (PCA) based eye localization. Skin color segmentation is performed using statistical models for human skin color. The skin color segmentation task results in a mask marking the skin color regions in the actual frame, which is further used to compute the position and size of the dominant facial region utilizing a robust statistics-based localization method. To improve the results of skin color segmentation, a foreground/background segmentation and an adaptive background update scheme are added. Additionally, the derived face position is tracked with a Kalman filter. To overcome the problem of skin color ambiguity, an eye detection algorithm based on PCA is presented
Year
DOI
Venue
2001
10.1109/ICASSP.2001.941214
ICASSP
Keywords
Field
DocType
real-time face tracker,video signal processing,skin color region,kalman filter,object motion model,kalman filters,face recognition,statistical models,eye detection,eye localization,image segmentation,robust statistics-based localization method,skin color ambiguity,human skin color,real-time face tracking,feature extraction,face localization,pca,skin color detection,background segmentation,skin color segmentation task,skin color segmentation,principal component analysis,skin,color video,image colour analysis,image motion analysis,image analysis,pixel,face detection,statistical model,foreground background,robustness,algorithm design and analysis,robust statistics,real time
Computer vision,Facial recognition system,Pattern recognition,Color histogram,Segmentation,Computer science,Image segmentation,Feature extraction,Kalman filter,Pixel,Artificial intelligence,Face detection
Conference
Volume
ISSN
ISBN
3
1520-6149
0-7803-7041-4
Citations 
PageRank 
References 
24
1.69
3
Authors
2
Name
Order
Citations
PageRank
S. Spors1899.54
R. Rabenstein211915.00