Conference Proceeding

Automatic segmentation of training set for facial feature detection

Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London
10/1997; DOI:10.1109/ICICS.1997.652127 ISBN: 0-7803-3676-3 In proceeding of: Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Source: IEEE Xplore

ABSTRACT In conventional image-based feature detection a time consuming
pre-processing step is required to manually segment the training
features from the unsegmented face images. We present a novel method of
using automatically segmented facial image data for facial feature
detection. A quality measure is defined to identify those image data
from a large training set that are better to describe the feature. The
best quality subset is then extracted and used to train the feature
detector. The detection performance obtained by the automatically
segmented data set after refinement is almost as high as that obtained
by the feature detector trained by a manually segmented set

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Keywords

conventional image-based feature detection
 
feature detector
 
image data
 
large training
 
manually segment
 
manually segmented
 
novel method
 
pre-processing step
 
refinement
 
segmented data
 
segmented facial image data
 
unsegmented face images