title: HOG Detection methods
body: <p>i am new to Computer vision and Machine learning, i searched a lot but did not find quite answer for my questions.</p>
  <p>First: I want to know what is the difference between all of these detection methods.</p>
  <p>1)<code>HOG.detect()</code></p>
  <p>2)<code>HOG.detectMultiScale()</code></p>
  <p>3)<code>HOG.setSvmDetector()</code></p>
  <p>Second: I read that <code>HOG.setSvmDetector()</code> used only for detecting one object since SVM is a binary classfication, i was wondering can we train  multi class SVM (One vs All) and for each single class of SVM we apply a new instance of <code>HOG.setSvmDetector()</code> ?</p>
  <p>for an examlpe if i constructed 2 SVM's which means now i have Multi class SVM of 2 classes can i do smth like this:</p>
  <blockquote>
  <p>HOGDescriptor hog1 = newHOGDescriptor()</p>
  <p>HOGDescriptor hog2 = new HOGDescriptor()</p>
  <p>hog1.setSvmDetector( CLASS ONE )</p>
  <p>hog2.setSvmDetector( CLASS TWO )</p>
  </blockquote>