Abstract
An algorithm for the estimation of chin and cheek contours in video sequences is proposed. This algorithm exploits a priori knowledge about shape and position of chin and cheek contours in images. Exploiting knowledge about the shape, a parametric 2D model representing chin and cheek contours is introduced. Exploiting knowledge about the position, a MAP estimator is developed taking into account the observed luminance gradient as well as a priori probabilities of chin and cheek contours positions. The proposed algorithm was tested with head and shoulder video sequences (image resolution CIF). In nearly 70% of all investigated video frames, a subjectively error free estimation could be achieved. The 2D estimate error is measured as on average between 2.4 and .
Highlights
Techniques for estimation of facial features like eyes, mouth, nose, eyebrows, chin and cheek contours are essential for various types of applications [1, 2, 3, 4, 5, 6, 7, 8]
A new parametric 2D model representing chin and cheek contours is introduced. This 2D model consists of four parabola pieces which are linked together
The proposed algorithm for chin and cheek contours estimation is tested with head and shoulder videophone sequences and its performance is evaluated
Summary
Techniques for estimation of facial features like eyes, mouth, nose, eyebrows, chin and cheek contours are essential for various types of applications [1, 2, 3, 4, 5, 6, 7, 8]. Algorithms for chin and cheek contours estimation use a priori knowledge about shape and position only to a limited extent. A snake is an energy-minimizing spline influenced by image features to pull it toward edges These approaches were applied to persons looking straight into the camera. A priori knowledge about the typical shape and probable positions of chin and cheek contours is exploited in many ways. A new parametric 2D model representing chin and cheek contours is introduced. Assuming video sequences with a quite small face size, this model allows an exact localization of chin and cheek contours with a low number of parameters to be estimated.
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