Moving objects are often the most interesting parts in image sequences. When images from a camera are undersampled and the moving object is depicted small on the image plane, processing afterwards may help to improve the visibility as well as automatic recognition of the object. This paper presents an approach which performs Super-Resolution (SR) specifically on small moving objects. The presented approach estimates simultaneously a sub-pixel accurate boundary and an intensity description of the small moving object. This approach has the advantage that it permits explicit modeling of the partial volume effect for pixels which are influenced by both the moving object and the background of the scene. This paper describes the setup of the proposed SR algorithm for small moving objects and shows its superior performance in comparison with a standard SR approach.