In Augmented Reality, computer generated information can assist the userwith 'invisible' information about real world objects. In this thesis, thepossibilities for Augmented Reality on mobile devices will be investigated,and Object Tracking is identied as a vital functionality. In the existing so-lutions, position- and orientation-based tracking is most common, however,this project will approach vision-based tracking, which is a wide researcharea in the eld of Computer Vision.The chosen object tracker, is the prize-awarded algorithm TLD, which together with the recently released FastCVlibrary, makes up the functionality in the nal presented application. Theapplication is tested with regard to memory and processing time, and it is observed from the experiments, that the Detector module in TLD domi-nates the processing time. Nonetheless, the nal Object Tracker performsas intended and decent frame rates is obtained by reducing the size of thecamera image frame.For further work, the processing time could be reduced even more, possiblyby making a longer interval between each run with the detector module.Also the possibility to save object models and use them later on should beexplored. This would be useful in an Augmented Reality application, wherethe objects usually is predetermined.