Computer Vision — Detecting objects using Haar Cascade Classifier
OpenCV (Open Source Computer Vision Library: http://opencv.org) is an open-source BSD-licensed library that includes several hundreds of computer vision algorithms.
Haar Cascade Classifiers : We will implement our use case using the Haar Cascade classifier. Haar Cascade classifier is an effective object detection approach which was proposed by Paul Viola and Michael Jones in their paper, “Rapid Object Detection using a Boosted Cascade of Simple Features” in 2001.
So, let’s try to understand what these Haar Cascade Classifiers are.This is basically a machine learning based approach where a cascade function is trained from a lot of images both positive and negative. Based on the training it is then used to detect the objects in the other images.
So how this works is they are huge individual .xml files with a lot of feature sets and each xml corresponds to a very specific type of use case.
For Example, if you go to the github page of haarcascade you will see that there is a particular xml file containing the feature set to detect the full body, lower-body, eye, frontal-face and so on.
To understand how the haar cascade classifier work and how will that be used for computer vision, let’s implement some of the use cases.
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