Suppose I have a set of images that I will use for training. Just as an example take that I have pics of the same car in many different camera angles. I am required to identify the important features like the mirrors, the logo, may be some body features like curves, dents etc. These features have to be extracted from each of the pics (say manually or please suggest a better way) as these will be used for training. The task is I am given an arbitrary image of the same car in some unknown angle and I am to identify as many of the above features as possible. (It feels like an unsupervised learning problem) What procedure/algorithm should I follow? PS: I am new to the field of computer vision.
closed as too broad by David Richerby, Evil, D.W.♦ Oct 2 '16 at 0:02
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