Name
Abstract | ||
|---|---|---|
Recently, 3D landmark extraction has been widely researched and experimented in medical field, for both corrective and aesthetic purposes. Automation of these procedures on three-dimensional face renderings is something desirable for the specialists who work in this field. In this work we propose a new method for accurate landmark localization on facial scans. The method relies on geometrical descriptors, such as curvatures and Shape Index, for computing candidate and initial points, and on a statistical model based on Procrustes Analysis and Principal Component Analysis, which is fitted to candidate points, for extracting the final landmarks. The elaborated method is independent on face pose. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.cmpb.2012.07.008 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
accurate landmark localization,candidate point,final landmark,landmark extraction,medical field,three-dimensional face rendering,face landmark formalization,elaborated method,principal component analysis,procrustes analysis,pose-independent method,new method,differential geometry,pca | Computer vision,Shape index,Pattern recognition,Computer science,Procrustes analysis,Automation,Artificial intelligence,Statistical model,Differential geometry,Landmark,Rendering (computer graphics),Principal component analysis | Journal |
Volume | Issue | ISSN |
108 | 3 | 1872-7565 |
Citations | PageRank | References |
6 | 0.49 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrico Vezzetti | 1 | 151 | 12.98 |
| Sandro Moos | 2 | 17 | 2.02 |
| Federica Marcolin | 3 | 94 | 7.50 |
| Vincenzo Stola | 4 | 13 | 1.37 |