Name
Abstract | ||
|---|---|---|
This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIP.2016.2518867 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Face,Shape,Vegetation,Detectors,Feature extraction,Regression tree analysis,Training | Computer vision,Pattern recognition,Computer science,Principle of locality,Feature extraction,Frame rate,Artificial intelligence,Initialization,Face detection,Discriminative model,Detector,Binary number | Journal |
Volume | Issue | ISSN |
25 | 3 | 1057-7149 |
Citations | PageRank | References |
25 | 0.74 | 39 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shaoqing Ren | 1 | 17051 | 548.00 |
| Xudong Cao | 2 | 1231 | 38.97 |
| Yichen Wei | 3 | 2074 | 67.87 |
| Jian Sun | 4 | 25842 | 956.90 |