Name
Abstract | ||
|---|---|---|
Face detection is a challenging research area and crucial step of face detection system. Because of the factors of rotation, pose change, and complicated background, false faces also can be found in detection results. This paper puts forward a new approach based on the landmark localization to detect face image which includes various pose variation. Furthermore, the proposed histogram of sparse code-based method is very effective and it can capture global elastic and multi-view deformation which can be optimized easily. The proposed method achieved higher effectiveness and efficiency in comparison with the existing face detection methods on different data sets. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICMLC.2016.7873015 | 2016 International Conference on Machine Learning and Cybernetics (ICMLC) |
Keywords | Field | DocType |
Face detection,Deformable part model,Sparse code | Computer vision,Histogram,Data set,Pattern recognition,Object-class detection,Computer science,Feature extraction,Artificial intelligence,Face detection,Landmark,Machine learning | Conference |
Volume | ISBN | Citations |
2 | 978-1-5090-0391-4 | 2 |
PageRank | References | Authors |
0.38 | 11 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qi Zhang | 1 | 931 | 179.66 |
| Lifang Zhou | 2 | 29 | 11.08 |
| Weisheng Li | 3 | 141 | 29.73 |
| Karl Ricanek | 4 | 165 | 18.65 |
| Xinyi Li | 5 | 21 | 5.87 |