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arXiv · 1812.10306

Spotting Micro-Expressions on Long Videos Sequences

Jingting Li·Catherine Soladie·Renaud Sguier·Sujing Wang·Moi Hoon Yap
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Abstract

This paper presents baseline results for the first Micro-Expression Spotting Challenge 2019 by evaluating local temporal pattern (LTP) on SAMM and CAS(ME)2. The proposed LTP patterns are extracted by applying PCA in a temporal window on several facial local regions. The micro-expression sequences are then spotted by a local classification of LTP and a global fusion. The performance is evaluated by Leave-One-Subject-Out cross validation. Furthermore, we define the criteria of determining true positives in one video by overlap rate and set the metric F1-score for spotting performance of the whole database. The F1-score of baseline results for SAMM and CAS(ME)2 are 0.0316 and 0.0179, respectively.

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Jingting Li, Catherine Soladie, Renaud Sguier, Sujing Wang, Moi Hoon Yap. 2019-07-13. Spotting Micro-Expressions on Long Videos Sequences. https://doi.org/10.1109/fg.2019.8756626

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