In the last decades, the growth of the GPS usage in many fields for outdoor localization has led to a higher demand of systems for indoor human localization for many fields of application, like home security or safety and healthcare. Creating an indoor localization system presents numerous challenges due to several characteristics that vary in every considered environment, such as room dimension, roof height, or furniture type and location. The recent improvements in the computer vision field given by machine learning algorithms can provide a possible solution to this problem, by using optical cameras that are able to follow human movements.