Facial boundary detection with an active contour model
This paper presents an active contour model for extracting accurate facial regions in complex environments. In the model, a contour is represented by a zero level set of level function ?, and evolved via level set partial differential equations. Then, unlike general active contours, skin-color information that is represented by 2D-Gaussian model is used for evolving and stopping a curve, which allows the proposed method to be robust to noise and varying pose. To assess the effectiveness of the proposed method, it was tested with several natural scenes, and the results were compared with those of geodesic active contours. Experimental results demonstrate the superior performance of the proposed method.
facial boundary detection active contour model level sets skin-color model markov random field