An Independent Evaluation of Subspace Face Recognition Algorithms
| dc.creator | Surajpal, Dhiresh R. | |
| dc.creator | Marwala, Tshilidzi | |
| dc.date | 2007-05-07 | |
| dc.date.accessioned | 2026-07-07T07:59:49Z | |
| dc.date.available | 2026-07-07T07:59:49Z | |
| dc.description | This paper explores a comparative study of both the linear and kernel implementations of three of the most popular Appearance-based Face Recognition projection classes, these being the methodologies of Principal Component Analysis, Linear Discriminant Analysis and Independent Component Analysis. The experimental procedure provides a platform of equal working conditions and examines the ten algorithms in the categories of expression, illumination, occlusion and temporal delay. The results are then evaluated based on a sequential combination of assessment tools that facilitate both intuitive and statistical decisiveness among the intra and interclass comparisons. The best categorical algorithms are then incorporated into a hybrid methodology, where the advantageous effects of fusion strategies are considered. | |
| dc.description | 7 pages | |
| dc.identifier | https://arxiv.org/abs/0705.0952 | |
| dc.identifier | http://arxiv.org/abs/0705.0952 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/128511 | |
| dc.subject | Computer Vision and Pattern Recognition | |
| dc.title | An Independent Evaluation of Subspace Face Recognition Algorithms | |
| dc.type | text |