This paper addresses the problem of tonal fluctuation in videos. Due to the automatic settings of consumer cameras, the colors of objects in image sequences might change over time. We propose here a fast and computa-tionally light method to stabilize this tonal appearance, while remaining robust to motion and occlusions. To do so, a minimally-viable color correction model is used, in conjunction with an effective estimation of dominant motion. The final solution is a temporally-weighted correction, explicitly driven by the motion magnitude, both visually efficient and very fast, with potential to real time processing. Experimental results obtained on a variety of sequences outperform the current state of the art in terms of tonal stability, at a much reduced computational complexity.