Name
Abstract | ||
|---|---|---|
Face recognition has become a popular topic due to its applications in security, surveillance and so on. Current local methods such as the local binary pattern (LBP) or local derivative pattern (LDP) perform better than holistic methods since they are more stable on local changes such as misalignment, expression or occlusion, but their high computational complexity limit their applications. While ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1049/iet-ipr.2016.1074 | IET Image Processing |
Keywords | Field | DocType |
computational complexity,face recognition,transforms | Computer vision,Scale-invariant feature transform,Facial recognition system,Histogram,Pattern recognition,Local binary patterns,Execution time,Artificial intelligence,Maxima,Mathematics,Computational complexity theory,Binary descriptor | Journal |
Volume | Issue | ISSN |
11 | 12 | 1751-9659 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jou Lin | 1 | 0 | 0.34 |
| Ching-Te Chiu | 2 | 304 | 38.60 |