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2013-04-14 18:48:31 -0600	commented answer	haar classifier detection vs feature detection,extraction and matching Thanks for your suggestions!!
2013-04-13 11:37:35 -0600	commented answer	haar classifier detection vs feature detection,extraction and matching Thanks Guanta. I should have mentioned my use case in the question, sorry about that. My aim is to only detect the presence of an object, like a human in the scene, car in the scene, bicycle in the scene so on. I do not need to be more specific in terms of what exactly is the detected object (not required to tell if the car is say audi or bmw or mustang or whatever). From the answers, I understand that object detection can be done using the different classifier techniques. But, you also mention that keypoint-detectors and descriptor-extractors can be used for same purpose. Could you please tell me if that is the case, for my purposes of just detecting the presence of an object (accurate information is not required), which approach would be better?
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2013-04-13 11:27:35 -0600	commented answer	haar classifier detection vs feature detection,extraction and matching Thanks Steven. That makes more sense to me now. My purpose is only to detect objects and I do not need to recognize what exactly it is. So from the explanation I understand that I can do this using cascade classifier or svm classifier or random forest classifier. I do not need to consider using the keypoint detection-descriptor extraction-descriptor matching method for now.
2013-04-13 02:48:41 -0600	asked a question	haar classifier detection vs feature detection,extraction and matching Hi, I have started using opencv from past few weeks. I am learning about ways of doing object detection. I see that there are primarily 2 different approaches to do object detection: Use positive and negative image set, build classifier and use the classifier to detect objects Use the keypoint detection, descriptor extraction and matching to detect objects I would like to know when to apply which technique? I also found that the 2nd method internally has multiple algorithms to do each step like SIFT, SURF, ORB, FlannMatcher so on. My primary aim is to first understand when to use classifier technique and when to use feature extraction technique? Once I understand that, I can further look at the different approaches within them. Please correct me if my understanding above is wrong and let me know the differences between the 2 approaches.