Attractor-Guided Particle Filtering for Lip Contour Tracking

We present a lip contour tracking algorithm using attractor-guided particle filtering. Usually it is difficult to robustly track the lip contour because the lip contour is highly deformable and the contrast between skin and lip colors is very low. It makes the traditional blind segmentation-based algorithms often fail to have robust and realistic results. But in fact, the lip contour is constrained by the facial muscles, the tracking configuration space can then be represented by a lower dimensional manifold. With this observation, we take some representative lip shapes as the attractors in the lower dimensional manifold. To resolve the low contrast problem, we adopt a color feature selection algorithm to maximize the separability between skin and lip colors. Then we integrate the shape priors and the discriminative feature into the attractor-guided particle filtering framework to track the lip contour. The experimental result shows that we can track the lip contour robustly and efficiently.