Implemented a heat map generator based on computer vision techniques to stochastically estimate the most visited areas in an indoor space with a monocular camera. A feature tracker method was used to estimate the average flow of persons and a deep convolutional neural network was employed to obtain the segmentation of the floor in the scene. This information was merge together to ​gather relevant information about the people habits in shopping centers or crowded areas (Implemented in Python/ Linux)