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 | 1 | initial version |
The detectMultiscale method does not return any confidence factor, however, depending on your application, it might be possible to achieve one without recurring to complex methodologies. If detection is being performed at multiple scales, it is expected that, in some cases, the same object is detected more than once in the same image. So, it is safe to assume that an object detected 2 times has a higher confidence measure that one that was detected one time. In the detectMultiscale method pass the minNeighbours argument as 0 so the algorithm doesn't aggregate any detections.
If you are detecting in sequential frames from a still camera, you can even create your own confidence evaluator algorithm. If the same object is detected multiple times in a number of sequential frames, it is assumed that this object has a higher confidence level, whereas if an object is detected in some frames but not in others, it has a less confidence measure. Be creative.
| | 2 | No.2 Revision |
The detectMultiscale method does not return any confidence factor, however, depending on your application, it might be possible to achieve one without recurring to complex methodologies.
If detection is being performed at multiple scales, it is expected that, in some cases, the same object is detected more than once in the same image. So, it is safe to assume that an object detected 2 times has a higher confidence measure that than one that was detected one time. In the detectMultiscale method pass the minNeighbours argument as 0 so the algorithm doesn't aggregate any detections.
If you are detecting in sequential frames from a still camera, you can even create your own confidence evaluator algorithm. If the same object is detected multiple times in a number of sequential frames, it is assumed that this object has a higher confidence level, whereas if an object is detected in some frames but not in others, it has a less confidence measure. Be creative.
