Machine learning models in people detection and identification

Introduction: This article is the result of research entitled "Development a prototype to optimize access conditions SENA-Pescadero using artificial intelligence and open-source tools", developed at Servicio Nacional de Aprendizaje in 2020. Problem: How identify Machine Learning Techniques applied computer vision processes through literature review? Objective: Determine application, as well advantages disadvantages machine learning techniques focused on detection identification people. Methodology: Systematic review 4 high-impact bibliographic scientific databases, search filters information selection criteria. Results: defined Principal Component Analysis, Weak Label Regularized Local Coordinate Coding, Support Vector Machines, Haar Cascade Classifiers EigenFaces FisherFaces, their applicability processes. Conclusion: The led main computational based learning, Their influence was shown several application cases, but most them were implementation optimization control systems, or tasks which people required for execution Originality: Through this research, we studied currently used Limitations: systematic limited available databases consulted, amount variable articles are deposited databases.