Name
Abstract | ||
|---|---|---|
To tackle the problem of automatic recognition of human eyebrow, a novel approach for shape analysis based on frontal face images is proposed in this paper First, eyebrow curves are acquired by fitting cubic splines based on landmark points. Next, we propose to use a modified functional curve procrustes distance to measure the similarities among the cubic splines, and finally a multidimensional scaling method is adopted to evaluate the effectiveness of the distance. This work extends previous work in analyzing the eyebrow for both human and machine recognition by providing a framework based on shape contours. Further this work demonstrates the effectiveness of eyebrow shape for discrimination when teamed with the appropriate metric distance. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/BTAS.2013.6712741 | 2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS) |
Keywords | Field | DocType |
face recognition | Spline (mathematics),Computer vision,Facial recognition system,Pattern recognition,Multidimensional scaling,Metric (mathematics),Eyebrow,Artificial intelligence,Landmark,Mathematics,Procrustes,Shape analysis (digital geometry) | Conference |
Citations | PageRank | References |
2 | 0.37 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yishi Wang | 1 | 43 | 5.50 |
| Cuixian Chen | 2 | 53 | 6.38 |
| A. Midori Albert | 3 | 2 | 0.37 |
| Yaw Chang | 4 | 34 | 3.31 |
| Karl Ricanek | 5 | 165 | 18.65 |