Dense non-rigid visual tracking with a robust similarity function
This paper deals with dense non-rigid visual tracking robust towards global illumination perturbations of the observed scene. The similarity function is based on the sum of conditional variance (SCV). With respect to most approaches that minimize the sum of squared differences, which is poorly robust towards illumination variations in the scene, the choice of SCV as our registration function allows the approach to be naturally robust towards global perturbations. Moreover, a thin-plate spline warping function is considered in order to take into account deformations of the observed template. The proposed approach, after being detailed, is tested in nominal conditions and on scenes where light perturbations occur in order to assess the robustness of the approach.