Class OpenCVFilterEyeLocator
source code
This class is used for someone only interested in locating the eyes in
an image using correlation filters. This class does not include any
support for training correlation filters. For training see ASEF. This
class is written only using OpenCV and is much faster than the ASEF
class.
For details see the paper:
David S. Bolme, Bruce A. Draper, and J. Ross Beveridge. Average of
Synthetic Exact Filters. Submitted to Computer Vision and Pattern
Recoginition. 2009.
The class uses two ASEF filters to find the eyes. The eyes are
located by first computing the correlation of the face tile with each
filter. The max value from the correlation plain is returned as the eye
coordinate. Also returned is the full correlation output from the
image.
The images are normalized by computing log transforming the pixel
values
To improve performance, this class is not thread safe. The class
reuses data arrays allocated for each call to use this class for multiple
threads you should create an instance for each threads. Also note that
each method call may overwrite arrays returned by this application. So
if you need the returned data to persist be sure to create a copy.
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Left and right eyes are in relation to the location in the image.
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locateEyes(self,
image_tile)
Returns:
a tuple consisting of the location of the left and right eyes (opencv
2D points), and the complex correlation plain output |
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_preprocess(self,
image_tile)
preprocess an image tile. |
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correlate(self,
image_tile)
Correlate the image with the left and right filters. |
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__init__(self,
left_filter,
right_filter,
left_rect,
right_rect)
(Constructor)
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- Parameters:
left_filter - is in the Fourier domain where the left eye corresponds to the
real output and the right eye corresponds to the imaginary output
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- Parameters:
image_tile (8-bit gray scale opencv image) - is an 32-bit gray scale opencv image tile of a face that is the
same size as the filter - Returns:
- a tuple consisting of the location of the left and right eyes
(opencv 2D points), and the complex correlation plain output
- Raises:
AssertionError - is raised if the image is not 8-bit or not the same size as the
filter
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