Using scene specific knowledge and constraints to optimize the detection result

Once your cascade classifier object model is trained, you can use it to detect instances of the same object class in new input images, which are supplied to the system. However, once you apply your object model, you will notice that there are still false positive detections and objects that are not found. This section will cover techniques to improve your detection results, by removing, for example, most of the false positive detections with scene-specific knowledge.

Using the parameters of the detection command to influence your detection result

If you apply an object model to a given input image, you must consider several things. Let's first take a look at the detection function and some of the parameters that can be used to filter out your detection output. OpenCV 3 supplies three possible interfaces. We will discuss the benefits of using each one of them.

Interface 1:

void CascadeClassifier::detectMultiScale...