Name
Abstract | ||
|---|---|---|
This paper presents a new framework for facial expression recognition based on diffeomorphic matching. First landmarks are selected based on a manual or automatic method. All of the landmarks from different images are registered to a reference landmark set using a rigid registration algorithm. The pair-wise geodesic distance between all sets of landmarks are then computed using diffeomorphic matching. Finally, a K-Nearest Neighbor classifier (KNN) is used to classify a query image using the geodesic distances. Both the classification and classical MultiDimensional Scaling results show that geodesic distance is more effective than Euclidean distance on capturing the face shape variation. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5650670 | Image Processing |
Keywords | Field | DocType |
face recognition,image matching,pattern classification,diffeomorphic matching,facial expression recognition,geodesic distance,k nearest neighbor classifier,multidimensional scaling,query image,Diffeomorphism,Expression detection,Face recognition,Geodesic distance | Facial recognition system,Computer vision,Pattern recognition,Multidimensional scaling,Facial expression recognition,Computer science,Euclidean distance,Artificial intelligence,Classifier (linguistics),Landmark,Geodesic,Diffeomorphism | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 6 |
PageRank | References | Authors |
0.47 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siamak Yousefi | 1 | 86 | 13.41 |
| Minh Phuoc Nguyen | 2 | 6 | 0.47 |
| Nasser D. Kehtarnavaz | 3 | 16 | 1.42 |
| Yan Cao | 4 | 29 | 1.78 |