This bachelor thesis implements a system for camera tracking based on a particle filter. For this purpose, a marker tracking is realized and the camera position is calculated based on the marker position. The marker is to be found with a particle filter and in order to accomplish this possible marker positions are simulated, also called particles, and weighted with Likelyhood-Functions. The focus lies on the evaluation of different Likelihood-Functions of the particle filter. The Likelyhood functions were implemented in CUDA as part of the implementation.