2026-04-17T03:35:47Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4709262025-06-12T11:08:04Zcom_2072_98col_2072_378192

A Spatio-Temporal Spotting Network with Sliding Windows for Micro-Expression Detection Fu, Wenwen An, Zhihong Huang, Wendong Sun, Haoran Gong, Wenjuan Gonzàlez, Jordi Micro-expressions reveal underlying emotions and are widely applied in political psychology, lie detection, law enforcement and medical care. Micro-expression spotting aims to detect the temporal locations of facial expressions from video sequences and is a crucial task in micro-expression recognition. In this study, the problem of micro-expression spotting is formulated as micro-expression classification per frame. We propose an effective spotting model with sliding windows called the spatio-temporal spotting network. The method involves a sliding window detection mechanism, combines the spatial features from the local key frames and the global temporal features and performs micro-expression spotting. The experiments are conducted on the CAS(ME) (Formula presented.) database and the SAMM Long Videos database, and the results demonstrate that the proposed method outperforms the state-of-the-art method by (Formula presented.) for the CAS(ME) (Formula presented.) and (Formula presented.) for the SAMM Long Videos according to overall F-scores. 2023 Article Agencia Estatal de Investigación PID2020-120311RB-I00 Electronics ; Vol. 12, Issue 18 (September 2023), art. 3947 open access Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. https://creativecommons.org/licenses/by/4.0/