2016-01-23 10:24:59 -0600 | received badge | ● Editor (source) |
2016-01-21 11:17:51 -0600 | asked a question | How does OpenCV detect objects using LBP features? I understand that once you train a classifier in OpenCV it generates an XML file with the stages and features, etc. I have been able to understand the format of the classifier and the function of every component from this page. However, I am not sure how the lookup table (LUT as referenced in this link) is computed, how does this relate to an lbp histogram used for classification? I understand that the I am also not sure of exactly how it is scaling different sub-windows and evaluating features within it. How are the exact features and offsets evaluated within the context of different sub-windows and how does a candidate sub-window then get accepted? I have looked inside the files in the folder: modules/objdetect/src/ but I am not able to see where the logic for any of this is as the code is very abstracted. |