Micro-Expression Spotting Using the Riesz Pyramid

Facial micro-expressions (MEs) are fast and involuntary facial expressions which reveal people hidden emotions. ME spotting refers to the process of finding the temporal locations of rapid facial movements from a video sequence. However, detecting these events is difficult due to their short durations and low intensities. Also, a distinction must be made between MEs and eye-related movements (blinking, eye-gaze change, etc). Taking inspiration from video magnification techniques, we design a workflow for automatically spotting MEs based on the Riesz pyramid. In addition, we propose a filtering and masking scheme that segment motions of interest without producing undesired artifacts or delays. Furthermore, the system is able to differentiate between MEs and eye movements. Experiments are carried out on two databases containing videos of spontaneous micro-expressions. Finally, we show that our method is able to outperform other methods from the state of the art in this challenging task.