Background robust face tracking using active contour technique combined active appearance model

Authors:
Jaewon Sung;Daijin Kim
Affiliations:
Biometrics Engineering Research Center (BERC), Pohang University of Science and Technology;Biometrics Engineering Research Center (BERC), Pohang University of Science and Technology
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

Citing 5
Cited 1

CONDENSATION—Conditional Density Propagation forVisual Tracking

International Journal of Computer Vision
Active Appearance Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Active Appearance Models

ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Interpreting Face Images Using Active Appearance Models

FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
An iterative image registration technique with an application to stereo vision

IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2

Robust face tracking by integration of two separate trackers: Skin color and facial shape

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a two stage AAM fitting algorithm that is robust to the cluttered background and a large motion. The proposed AAM fitting algorithm consists of two alternative procedures: the active contour fitting to find the contour sample that best fits the face image and then the active appearance model fitting over the best selected contour. Experimental results show that the proposed active contour based AAM provides better accuracy and convergence characteristics in terms of RMS error and convergence rate, respectively, than the existing robust AAM.