Motion is one of the biggest challenges in clinical MRI. The recently introduced Magnetic Resonance Fingerprinting (MRF) has been shown to be less sensitive to motion. However, it is still susceptible to patient motion primarily occurring in the early stages of the acquisition. In this study, we propose a novel reconstruction algorithm for MRF, which decrease the motion sensitivity of MRF. The evaluation of the algorithm was performed using simulated head tilt and nodding motion, and with prospectively motion corrupted data from healthy volunteers.