Tracking and Train SVM detector with HOG features online

Support vector machine with Histogram of oriented gradient trained near online, and tracker. 
support vector machine with HOG tracker


Building the SVM detector based on the HOG feature is a relatively simple process. When is not necessary to be robust and detector is focused only on one object. You can build this by combining several OpenCV available tutorials and source codes distributed in Opencv samples. There is maybe one thing that is not natural and cannot be taken from examples and tutorials. Train set in online training is only 20 positive images warp over positive windows and 30 random negative samples.

What do you think? 

Tutorial on SVM with HOG, tracker soon


This is just an example. The tutorial will be available later. The code is a little bit complex.


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3 Comments
  • Unknown
    Unknown April 21, 2017 at 7:27 PM

    Hey,
    Can you share the code , I'm trying to use SVM with HOG to track and recognize people in a surveillance system. The method you followed could be a great head start for my project!

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