Im using opencv_traincascade with a one stage classifier. I don't really know how it works but it seems like it guesses at rectangles ('features' in CV terminology?) to try and divide the positive samples from the negative sample.
* HR is hit rate - the proportion of positive samples that are (correctly) passed though.
* FA is false alarm rate - the proportion of negative samples that are (incorrectly) passed though.
Is my understanding correct?
My output is looks like this:
===== TRAINING 0-stage =====
<BEGIN
POS count : consumed 27 : 27
NEG count : acceptanceRatio 416 : 1
Precalculation time: 3
+----+---------+---------+
| N | HR | FA |
+----+---------+---------+
| 1| 1| 1|
+----+---------+---------+
| 2| 1| 1|
+----+---------+---------+
| 3| 1|0.0576923|
+----+---------+---------+
| 4| 1|0.00480769|
+----+---------+---------+
END>
Why does it not ignore feature/node/rectangle number 1 and number 2 since they appear to simply let though everything?