Occlusions and cluttered environments represent real challenges for visual tracking methods. In order to in-crease robustness for such situations, we present, in this article, a method for visual tracking using a Particle Filter with Hybrid Resampling. Our approach consists of using a particle filter to estimate the state of the tracked object, and both particles' inertia and update information are used in the resampling stage. The pro-posed method is tested using a public benchmark and the results are compared with other tracking algorithms. The results show that our approach performs better in cluttered environments, as well as in situations with total or partial occlusions.