Name
Title | ||
|---|---|---|
Improvements and Performance Evaluation Concerning Synthetic Age Progression and Face Recognition Affected by Adult Aging |
Abstract | ||
|---|---|---|
Aging of the face degrades the performance of face recognition algorithms. This paper presents recent work in synthetic age progression as well as performance comparisons for modern face recognition systems. Two top-performing, commercial systems along with a traditional PCA-based face recognizer are compared. It is shown that the commercial systems perform better than the baseline PCA algorithm, but their performance still deteriorates on an aged data-set. It is also shown that the use of our aging model improves the rank-one accuracy in these systems. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01793-3_7 | ICB |
Keywords | Field | DocType |
rank-one accuracy,face recognition,synthetic age progression,modern face recognition system,performance comparison,face recognition algorithm,performance evaluation,adult aging,commercial system,traditional pca-based face recognizer,recent work,aged data-set,baseline pca algorithm,system performance | Age progression,Facial recognition system,Computer vision,Computer science,Speech recognition,Artificial intelligence | Conference |
Volume | ISSN | Citations |
5558 | 0302-9743 | 7 |
PageRank | References | Authors |
0.74 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amrutha Sethuram | 1 | 17 | 3.41 |
| Eric Patterson | 2 | 9 | 1.82 |
| Karl Ricanek | 3 | 165 | 18.65 |
| Allen Rawls | 4 | 7 | 0.74 |