  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.
