Home How do I apply a sliding window technique on images for multiple people detection?
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How do I apply a sliding window technique on images for multiple people detection?

joe
1#
joe Published in 2018-02-13 09:59:08Z

I am implementing HOG for people detecting and SVM Classifier has been trained.But I am not aware on how to use that pretrained classifier for detection using sliding window technique.Please someone guides me to build a sliding window technique for multiple people detection in Matlab.

Shawn Mathew
2#
Shawn Mathew Reply to 2018-02-14 16:07:51Z

The python tutorial over here should give you an idea on how to implement this.

The basic idea is for each window, compute the hog descriptors (using opencv, for example) and then multiply element-wise the HOG descriptors with the trained SVM weights (They should be the same size). After multiplying, add the bias (which is another output from the SVM classifier) to the previous result. If the result is positive, it's a positive match, otherwise it's a negative match.

Note: the sliding window size is the same size as the training images.

So,

for each pixel in the image:
   get a sub-image of size of sliding window
   compute the HOG descriptors for this image
   product = hog * SVM_weights //element-wise multiplication
   response = product + bias
   if response > 0:
       print "match"
   else:
       print "no match"
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