Classification of OpenCV cascades with characteristic oriented gradient histogram (HOG) type
I'm trying to use an OpenCV cascade classifier based on an oriented object histogram (HOG) object type - for example, the document Fast Human Detection Using Oriented Gradient Histogram Cascade.
Searching the internet I found that the OpenCV Cascade Classificationator only supports the HAAR / LBP ( OpenCV Cascade Classification ) function type .
- Is there a way to use HOG with OpenCV cascading classifier? What do you suggest?
- Is there a patch or other library I can use?
Thanks in advance!
EDIT 1
I saved my search when I finally found in android-opencv that the Cascade Classifier has a connector that allows it to work with HOG features. But I don't know if this works ...
Link: http://code.opencv.org/projects/opencv/repository/revisions/6853
EDIT 2
I have not tested the fork above because my problem has changed. But I found an interesting link that might be very helpful in the future (when I come back to this issue).
This page contains the source code for Oriented Gradient Histograms for Human Detection. Also more information. http://pascal.inrialpes.fr/soft/olt/
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If you are using OpenCV-Python you have the option to use some additional libraries like scikits.image which have a histogram oriented inline gradients.
I had to solve this same problem a few months ago and have documented most of the work (including very simple Python implementations for HoG and GPU HoG implementations using PyCUDA) on this project page . The code is there. The GPU code should be easily modified for use in C ++.
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Yes, you can use cv::CascadeClassifier
with functions HOG
. To do this, simply download it with the help hogcascade_pedestrians.xml
that you can find in opencv_src-dir/data/hogcascades
.
The classifier is faster and its results are much better when trained with the aid hogcascade
compared to haarcascade
...
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