For object deteciton results in:
- Haar Cascade (Especially)
- LBP Cascade
- HOG Descriptor
-
- anything else
The resullt of the detection is a number. For example for Haar Cascade, it is a floating point number (with fractinal part). e.g. 12.987654321. And also i have seen it range from at least some negative value (e.g. -1.0123) to a positive (e.g 4.519985).
So to evaluate how ‘good’ a result this is, what is the Minimum and Maximum possible values that the result can be (the range of the result)… Maybe It can be treated as a confidence value ?.
How is this value’s meaning to be interpreted when comparing the values of a detection produced from 2 cascade classifiers that each were trained to detect the same object (maybe they used different parameters, AND./OR training data, hence more than 1 classifier).
Also. how is this value’s meaning to be interpreted when comparing the values between 2 different cascade classifiers, each detecting differemt objects ?. (Can it be deduced that 1 classifier detection thier particular object more ‘surely’ than another, by comparing the value between the 2 calssifiers ?)
Also is there any meaning to the Negativeness of the value ? (Below 0)