An Overview of Camera-Based Methods for the Human Pose Estimation

This paper aims to provide an updated overview about the Human Pose Estimation (HPE), which is a typical Computer Vision-related problem. The review firstly analyzes the importance of the research topic, both in terms of number of publications and application fields. Thanks to the introduction of efficient machine learning techniques, nowadays HPE is feasible without the necessity of specialized and expensive instrumentations. The proposed review considers only the works based on the use of Machine Learning techniques, and it is divided in two parts: an analysis of methodologies presented for the 2D HPE and a similar one for the 3D HPE. Being this last generally approached as an extension of the 2D HPE, the Authors propose a section discussing the effective validity of the most diffused and open source 2D HPE methodologies. The review is concluded with a discussion about the main limitations of the procedures currently in use.