This paper describes an illumination and pose invariant face recognition system that is intended to be used in the automotive market for vehicle personalization. Near-infrared frame differencing improves the robustness to the outdoor illumination conditions. And we introduce the video-based recognition with pose clustering for pose invariant face recognition. We have collected large video dataset of drivers under various extreme outdoor illumination conditions. Experimental results show that the proposed method achieves high recognition rate with near-infrared frame differencing and pose clustering.