Understanding the SMPL model
As the acronym of SMPL suggests, this is a learned linear model trained on data from thousands of people. This model is built upon concepts from the Linear Blend Skinning model. It is an unsupervised and generative model that generates a 20,670-dimensional vector using the provided input parameters that we can control. This model calculates the blend shapes required to produce the correct deformations for varying input parameters. We need these input parameters to have the following important properties:
- It should correspond to a real tangible attribute of the human body.
- The features must be low-dimensional in nature. This will enable us to easily control the generative process.
- The features must be disentangled and controllable in a predictable manner. That is, varying one parameter should not change the output characteristics attributed to other parameters.
Keeping these requirements in mind, the creators of the SMPL model came...
