In general, there are two categories for object detection, in-
cluding machine learning-based approaches and deep learning-
based approaches. While deep learning techniques are ca-
pable of end-to-end object detection without using hand-
crafted features, most of them are computationally expensive
and resource-exhausting. This week, I have looked at opencv materials for object matching. The usage of a brute-force matcher is described below
Basics of Brute-Force Matcher
Brute-Force matcher takes the descriptor of one feature in first set and is matched with all other features in second set using some distance calculation. And the closest one is returned. Photo Credit: opencv.org
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