Name
Abstract | ||
|---|---|---|
This paper presents two methods for the first Micro-Expression Spotting Challenge 2019 by evaluating local temporal pattern (LTP) and local binary pattern (LBP) on two most recent databases, i. e. SAMM and CAS(ME)(2). First we propose LTP-ML method as the baseline results for the challenge and then we compare the results with the LBP-chi(2) distance method. The 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 LBP-chi(2)-distance method is to compare the feature difference by calculating chi(2) distance of LBP in a time window, the facial movements are then detected with a threshold. The performance is evaluated by Leave-One-Subject-Out cross validation. The overlap frames are used to determine the True Positives and the metric F1-score is used to compare the spotting performance of the databases. The F1-score of LTP-ML result for SAMM and CAS(ME)(2) are 0.0316 and 0.0179, respectively. The results show our proposed LTP-ML method outperformed LBP-chi(2)-distance method in terms of F1-score on both databases. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/FG.2019.8756626 | 2019 14TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2019) |
Field | DocType | Volume |
Expression (mathematics),Pattern recognition,Computer science,Local binary patterns,Artificial intelligence,Cross-validation,True positive rate,Spotting | Journal | abs/1812.10306 |
ISSN | Citations | PageRank |
2326-5396 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingting Li | 1 | 1 | 1.70 |
| Catherine Soladié | 2 | 23 | 6.27 |
| Renaud Séguier | 3 | 166 | 16.72 |
| Sujing Wang | 4 | 690 | 37.65 |
| Moi Hoon Yap | 5 | 190 | 27.82 |