Object tracking is a rapidly growing field in machine learning. Object tracking is exactly what name suggests, to keep tracking of an object. This method has all sorts of application in wide range of fields like military, household, traffic cameras, industries, etc. There are certain algorithms for the object tracking but the easiest one is color-based object detection. This is a color-based algorithm for object tracking supported very well in OpenCV library. OpenCV is an library popular among python developers, those who are interested in Computer vision. It is an open source library and hence anyone can use and modify it without any restrictions and licensing. The Color-based method of object tracking is fully supported by OpenCV's vast varieties of functions. There is little bit of simple math and an excellent logic behind this method of object tracking. But in simple language the target object is identified from and image given explicitly by user or some area selected from frame of video, and algorithm continuously search for that object from each frame in video and highlights the best match for every frame. But like every algorithm it also has some pros and cons which are discussed here.
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