Name
Title | ||
|---|---|---|
A Framework for Long Distance Face Recognition Using Dense - and Sparse-Stereo Reconstruction |
Abstract | ||
|---|---|---|
This paper introduces a framework for long-distance face recognition using both dense- and sparse-stereo reconstruction. Two methods to determine correspondences of the stereo pair are used in this paper: (a) dense global stereo-matching using maximum-a-posteriori Markov Random Fields (MAP-MRF) algorithms and (b) Active Appearance Model (AAM) fitting of both images of the stereo pair and using the fitted AAM mesh as the sparse correspondences. Experiments are performed regarding the use of different features extracted from these vertices for face recognition. A comparison between the two approaches (a) and (b) are carried out in this paper. The cumulative rank curves (CMC), which are generated using the proposed framework, confirms the feasibility of the proposed work for long distance recognition of human faces. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-10331-5_72 | ISVC (1) |
Keywords | Field | DocType |
active appearance model,proposed work,long distance recognition,long distance face recognition,proposed framework,human face,face recognition,sparse-stereo reconstruction,fitted aam mesh,long-distance face recognition,stereo pair,dense global stereo-matching,feature extraction,cumulant | Facial recognition system,Computer vision,Random field,Vertex (geometry),Pattern recognition,Computer science,Markov chain,Active appearance model,Stereo reconstruction,Artificial intelligence | Conference |
Volume | ISSN | Citations |
5875 | 0302-9743 | 3 |
PageRank | References | Authors |
0.47 | 19 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ham Rara | 1 | 47 | 4.05 |
| Shireen Elhabian | 2 | 14 | 2.37 |
| Asem Ali | 3 | 36 | 4.69 |
| Travis R. Gault | 4 | 14 | 1.54 |
| Mike Miller | 5 | 3 | 0.47 |
| Thomas Starr | 6 | 11 | 1.12 |
| Aly A. Farag | 7 | 2147 | 172.03 |