Name
Abstract | ||
|---|---|---|
This paper proposes a novel 3D Constrained Local Models (CLM) approach applied for the detection of facial landmarks in 3D images. This approach capitalizes on the properties of Independent Component Analysis (ICA) to define appropriate priors of a face Point Distribution Model. Tailored to the mesh manifold modality, this approach address the limitations of the depth images which require pose normalization and suffer from the loss of the shape information caused by 2D projection. We validate this framework through a series of experiments conducted with the public Bosporus database, whereby it demonstrates a competitive performance compared to other state of the art methods. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MWSCAS.2016.7869954 | 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS) |
Keywords | Field | DocType |
facial landmarks detection,3D constrained local model,CLM approach,3D images,independent component analysis,ICA,face point distribution model,mesh manifold modality,depth images,shape information loss,2D projection,public Bosporus database,pose normalization | Computer vision,Point distribution model,Normalization (statistics),Pattern recognition,Computer science,Independent component analysis,Artificial intelligence,Prior probability,Principal component analysis,Manifold | Conference |
ISSN | ISBN | Citations |
1548-3746 | 978-1-5090-0917-6 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marwa Chendeb El Rai | 1 | 0 | 0.34 |
| Claudio Tortorici | 2 | 16 | 5.98 |
| Al-Muhairi, H. | 3 | 4 | 2.91 |
| Naoufel Werghi | 4 | 326 | 41.99 |
| Marius George Linguraru | 5 | 362 | 48.94 |