Analyzing and temporally spotting motions which are almost invisible to the human eye might reveal interesting information about the world. However, detecting these events is difficult due to their short duration and low intensities. Taking inspiration from video magnification techniques, we design a workflow for analyzing and temporally spotting subtle motions based on the Riesz pyramid. In addition, we propose a filtering and masking scheme that segments motions of interest without producing undesired artifacts or delays. In order to be able to evaluate the spotting accuracy of our method, we introduce our own database containing videos of subtle motions. Experiments are carried out under different types and levels of noise. Finally, we show that our method is able to outperform other state of the art methods in this challenging task.