Towards automatic landmarking on 2.5D face range images
In this paper, we propose an algorithm to automatically landmark points on 2.5-dimensional (2.5D) face images. We applied the Scale-invariant Feature Transform (SIFT) method to a new automatic landmarking method. Automatic landmarking has a number of added advantages over manual landmarking and...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://ir.unimas.my/10168/ http://ir.unimas.my/10168/ http://ir.unimas.my/10168/1/Towards%20Automatic%20Landmarking%20on%202.5D%20Face%20Range%20Images%20%28abstract%29.pdf |
| Summary: | In this paper, we propose an algorithm to
automatically landmark points on 2.5-dimensional (2.5D) face
images. We applied the Scale-invariant Feature Transform
(SIFT) method to a new automatic landmarking method.
Automatic landmarking has a number of added advantages
over manual landmarking and it is more accurate and less time
consuming especially if the dataset is large. We developed an
interactive Graphical User Interface (GUI) tool to ease the
visualization of the extract face features, which are scale and
transformation invariant. The threshold values are then
analyzed and generalized to best detect and extract important
keypoints or/and regions of facial features. The results of the
automatic extracted keypoint features are shown in this paper. |
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