3D human body shape and pose estimation from RGB images is a challenging
problem with potential applications in augmented/virtual reality, healthcare
and fitness technology and virtual retail. Recent solutions have focused on
three types of inputs: i) single images, ii) multi-view images and iii) videos.
In this study, we surveyed and compared 3D body shape and pose estimation
methods for contemporary dance and performing arts, with a special focus on
human body pose and dressing, camera viewpoint, illumination conditions and
background conditions. We demonstrated that multi-frame methods, such as PHALP,
provide better results than single-frame method for pose estimation when
dancers are performing contemporary dances.

使用 RGB 图像进行三维人体形状和姿势估计是一个具有挑战性的问题，具有增强 / 虚拟现实、医疗保健和健身技术以及虚拟零售等潜在应用。本研究调查了并比较了当代舞蹈和表演艺术领域中的三维人体形状和姿势估计方法，重点关注人体姿势和着装、摄像机视角、光照条件和背景条件。我们证明了当舞者进行当代舞蹈表演时，多帧方法（如 PHALP）比单帧方法更能提供更好的姿势估计结果。