Name
Abstract | ||
|---|---|---|
So far, all studies investigating the facial expression of pain have validated methods on the same database, whereas the cross-database performance is less considered. This may be due to poor performance of well-trained models on other databases. In this paper, we propose two distinct methods to classify based on the temporal information. To explore the generalization capability of pain recognition models, we do cross-database validations on two benchmark pain databases: BioVid and X-ITE. We also experiment with combining both databases. Experimental results (1) show that our methods can be successfully used to classify pain (both methods perform similarly well), (2) demonstrate that the performance is robust by verifying them cross-database, and (3) present that the performance of pain assessment is improved with more data (combined-database). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ISPA.2019.8868562 | 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA) |
Keywords | Field | DocType |
cross-database,BioVid,X-ITE,pain assessment | Facial recognition system,Task analysis,Computer science,Pain assessment,Feature extraction,Facial expression,Artificial intelligence,Deep learning,Database | Conference |
ISSN | ISBN | Citations |
1845-5921 | 978-1-7281-3141-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ehsan Othman | 1 | 0 | 1.69 |
| Philipp Werner | 2 | 0 | 1.35 |
| Frerk Saxen | 3 | 0 | 0.34 |
| Ayoub Al-Hamadi | 4 | 474 | 67.09 |
| Steffen Walter | 5 | 127 | 13.34 |