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.

该论文探讨了人体建模和姿态估计的交叉领域，涉及计算机视觉、计算机图形学和机器学习，包括算法、方法学和实际应用，以及相关的传感器技术、2D 和 3D 人体建模方法学的挑战和进展，常用数据集和度量标准，以及未来的研究方向。该论文的主要贡献在于对 2D 和 3D 领域最先进的人体姿态估计算法的全面比较，旨在增进对 3D 人体建模和姿态估计的理解，并提供当前最先进成果、挑战和未来前景的见解。