Abstract | ||
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Face detection is a computer vision technique that detects the presence of a face in an image and calibrates it. In a natural scene, it is difficult for a face to be protected from occlusion. So a general face detection method is difficult to find a face because of the lack of facial features. This paper studies the face detection with large area occlusion. The underlying detection algorithm is the Adaboost cascade classifier based on the Haar-like feature. Firstly, the opencv cascade classifier is used to detect the human eye and the mouth. And then the face detection of the occlusion is realized, according to the relationship between the human eye and the human face and the relationship between the mouth and the face, which is the physiological characteristics of the face. Finally, the accuracy of large-area occlusion of various occluders is compared, which proves that the method is reasonable and robust. |
Year | DOI | Venue |
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2018 | 10.1109/CIS2018.2018.00031 | 2018 14th International Conference on Computational Intelligence and Security (CIS) |
Keywords | Field | DocType |
occlusion face detection,haar-like feature,adaboost cascade classier,facial features detection,facial physiology | Human eye,Computer vision,Occlusion,AdaBoost,Computer science,Cascading classifiers,Artificial intelligence,Face detection,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-7281-0170-5 | 0 | 0.34 |
References | Authors | |
3 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Zhuohao Guo | 1 | 0 | 0.34 |
Wei-Xing Zhou | 2 | 206 | 15.05 |
Luwei Xiao | 3 | 0 | 0.34 |
Xiaohui Hu | 4 | 17 | 8.10 |
Zehao Zhang | 5 | 0 | 0.34 |
Zhou Hong | 6 | 0 | 0.34 |