Method and system for customized detection tracking and counting of people

Abstract

Provided are computer-implemented technologies for crowd analysis. The technologies process input video footages of a crowd to detect people from the input, uniquely identify the detected people, track and count them across all the frames throughout the footages, classify them based on features of the identified people such as detected gender of the identified people. The technologies use customarily trained AI models that are specifically trained and retrained for detecting people in the local population that typically wear Arab style clothing. The learned models, through the training, quality controlling and retraining, attain the prediction capability for accurately detecting, identifying and classifying people from crowd scenes. The learned model, then, is applied to crowd analysis to provide detection and classification report of the crowd, which can be used for deeper analysis to fill various business/institutional needs.