Estimating 3D human pose and shape using SMPLify
In the previous section, you explored the SMPL model and used it to generate a 3D human body with a random shape and pose. It is natural to wonder whether it is possible to use the SMPL model to fit a 3D human body onto a person in a 2D image. This has multiple practical applications, such as understanding human actions or creating animations from 2D videos. This is indeed possible, and in this chapter, we are going to explore this idea in more detail.
Imagine that you are given a single RGB image of a person without any information about body pose, camera parameters, or shape parameters. Our goal is to deduce the 3D shape and pose from just this single image. Estimating the 3D shape from a 2D image is not always error-free. It is a challenging problem because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D (because multiple 3D poses can have the...
