Child and Adult Classification using OpenCV and Python
Aim of this article is to detect children and adults separately in digital images. While we employed our method, we applied Haar Cascades which is widely used technique in object detection. At first, we detected head and full body of pedestrians, then we used relative measurements. So we did proportioning head size to body size of pedestrians. By this technique, we tried to discriminate children and adults.We introduce our proposed algorithm which is used to detect children and adults in digital images.The algorithm consists of several steps, but it can be divided into two main parts. First part is detection of pedestrian and its face. Second is to calculate and determine the child and adult classifying.To detect pedestrian in digital image, it is trained with Haar-like feature by Adaboost algorithm which can be efficient and be used for pedestrian detection problem. In a digital image, there are various objects. To detect pedestrian or pedestrian’s head in digital images is applicable while ROI (Region of Interest) is pedestrian or pedestrians’ head. To implement, we used Haar Cascade detector.