Micro-Expression Spotting Based on Optical Flow Feature with Boundary Calibration

摘要

Micro-expressions, as a type of facial expression corresponding to macro-expressions, usually have a short duration and low intensity. Due to these characteristics, micro-expression spotting holds significant value in medical care and public safety. Recent years have witnessed advancements in micro-expression spotting methods; however, spotting micro-expressions remains a challenging task due to their brief duration and low intensity. In this paper, we propose a micro-expression spotting method based on optical flow features with boundary calibration. We first perform face detection, cropping, and alignment on images containing faces. Then, regions of interest (ROIs) are defined, and optical flow features are extracted. Furthermore, candidate expression segments are identified based on the magnitude of the processed optical flows. Finally, a boundary calibration module is utilized to calibrate the boundaries. The effectiveness of the proposed method is evaluated on the MEGC2024 test set, resulting in an overall F1-score of 0.27.