In this paper, we propose a particle filtering technique for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic equation which both depend on the image sequence. Taking into account several possible observations, the peculiar measure model we consider is a linear combination of Gaussian laws. Such a model allows us to infer an analytic expression of the optimal importance function used in the diffusion process of the particle filter. We demonstrate the significance of this model for a point tracking application. The resulting point tracker enables coping with trajectories undergoing abrupt changes, occlusion situations, large geometric deformations and noisy sequences. Its performances are shown on real world sequences.