Out-of-Plane rotated object detection using patch feature based classifier
In this paper, we presented a method to extend the weak classifiers that we have previously developed called the square patch feature for out-of-plane rotated object detection. The square patch feature is as discriminative as the popular Viola-Jones Haar-like classifier and is faster. Out-of-plane d...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/28270/ http://irep.iium.edu.my/28270/ http://irep.iium.edu.my/28270/ http://irep.iium.edu.my/28270/1/Out-of-Plane_Rotated_Object_Detection_using_Patch_Feature_based_Classifier.pdf |
| Summary: | In this paper, we presented a method to extend the weak classifiers that we have previously developed called the square patch feature for out-of-plane rotated object detection. The square patch feature is as discriminative as the popular Viola-Jones Haar-like classifier and is faster. Out-of-plane detection without any extra sample data is possible due to the point based representation of the patch feature. The feature points in the classifier data trained from a frontal face can be rotated by assuming that they are mapped on a surface of the object of interest. For simplification object of interest such as the face can be assumed to be flat. The method was tested for face detection problem. A face detector was trained using 4916 face images and rotated for out-of-plane detection. The detection rate of the out-of-plane detection is 71 with a false positive of 189. |
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