Confidence evaluation for cascade classifier in object detection

This paper proposed a method that can measure confidence for cascade classifier. It has great value in fusion of multi-classifier, sorting object detection results and so on. Differs from the traditional qualitative description results though using cascade classifier, this method could give a quantitative description for the results. Confidence evaluation function is constructed to calculate the confidence for the targets and the classifiers. Several experiments have been done and the results show that false alarm rate could be greatly reduced with little time cost.