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 :
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