Name
Abstract | ||
|---|---|---|
We describe a new face detection algorithm based on a hierarchy of support vector classifiers (SVMs). Some preprocessing steps reduce the number of candidates, which should be verifying by SVMs. Hierarchical SVMs are designed for coarse-to-fine search of human face. In the SVMS, eye classifiers with different complexity (measured by the number of support vector) are used to find the eye candidates. The gain for efficient computation is enormous. The proposed face detection system can also be used to detect multiple faces embedded in complicated background. In addition, this approach can be applied to different kinds of image variations such as face sizes, lighting conditions, and image qualities. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICME.2003.1221308 | ICME |
Keywords | Field | DocType |
coarse-to-fine search,image quality,face recognition,eye classifier,svm,different kind,different complexity,proposed face detection system,computational complexity,eye candidate,image classification,multiple faces,hierarchical face detection,face size,support vector classifier,hierarchical svms,face detection system,new face detection algorithm,human face,image variations,support vector machines,authentication,support vector,videoconference,face detection,skin | Structured support vector machine,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Object-class detection,Computer science,Support vector machine,Artificial intelligence,Face detection,Relevance vector machine,Contextual image classification | Conference |
Volume | ISBN | Citations |
3 | 0-7803-7965-9 | 0 |
PageRank | References | Authors |
0.34 | 11 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yao-Hong Tasi | 1 | 0 | 0.34 |
| Yea-shuan Huang | 2 | 479 | 79.42 |