DocumentCode
350783
Title
Automatic face feature tracking
Author
Jin, Kyung-Chan ; Cho, Jin-Ho
Author_Institution
Dept. of Electron. Eng., Kyungpook Nat. Univ., Taegu, South Korea
Volume
1
fYear
1999
fDate
1999
Firstpage
68
Abstract
A reliable face tracking can be obtained by integrating of the region detection, feature locating and tracking. To detect the face feature region, we used the mean shift method that is a clustering technique for multivariate data, and to track face landmark features, we also used the STK tracking method. STK tracking is very efficient for feature tracking, but the Newton-Raphson iteration scheme has the initial coordinate problem for tracking features. To solve the problem, we proposed a new BMA-NR method of the STK algorithm for face landmark features. Preliminary results indicate that this method solves the local minimum problem which occurs by NR iteration
Keywords
Newton-Raphson method; face recognition; feature extraction; tracking; BMA-NR method; Newton-Raphson iteration scheme; STK tracking method; automatic face feature tracking; clustering technique; face landmark features; feature locating; initial coordinate problem; local minimum problem; mean shift method; multivariate data; region detection; Clustering algorithms; Computer vision; Convergence; Equations; Face detection; Feature extraction; Kernel; Reliability engineering; Robustness; Skin;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 99. Proceedings of the IEEE Region 10 Conference
Conference_Location
Cheju Island
Print_ISBN
0-7803-5739-6
Type
conf
DOI
10.1109/TENCON.1999.818351
Filename
818351
Link To Document