Human modelling and pose estimation stands at the crossroads of Computer Vision, Computer Graphics, and Machine Learning. This paper presents a thorough investigation of this interdisciplinary field, examining various algorithms, methodologies, and practical applications. It explores the diverse range of sensor technologies relevant to this domain and delves into a wide array of application areas. Additionally, we discuss the challenges and advancements in 2D and 3D human modelling methodologies, along with popular datasets, metrics, and future research directions. The main contribution of this paper lies in its up-to-date comparison of state-of-the-art (SOTA) human pose estimation algorithms in both 2D and 3D domains. By providing this comprehensive overview, the paper aims to enhance understanding of 3D human modelling and pose estimation, offering insights into current SOTA achievements, challenges, and future prospects within the field.

翻译：人体建模与姿态估计处于计算机视觉、计算机图形学和机器学习的交叉领域。本文对这一跨学科领域进行了全面研究，审视了各种算法、方法论及实际应用。文章探讨了与该领域相关的多种传感器技术，并深入研究了广泛的应用场景。此外，我们讨论了二维与三维人体建模方法面临的挑战与最新进展，同时涵盖了常用数据集、评估指标及未来研究方向。本文的主要贡献在于对当前最先进的二维与三维人体姿态估计算法进行了最新比较。通过提供这一全面概述，本文旨在深化对三维人体建模与姿态估计的理解，为该领域当前的最先进成果、挑战及未来前景提供见解。