SMPL

Skinned Multi-Person Linear model

https://youtu.be/kuBlUyHeV5U

SMPL is a realistic 3D model of the human body that is based on skinning and blend shapes and is learned from thousands of 3D body scans.

This site provides resources to learn about SMPL, including example FBX files with animated SMPL models,

and code for using SMPL in Python, Maya and Unity.

Abstract

We present a learned model of human body shape and pose-dependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines.

Our Skinned Multi-Person Linear model (SMPL) is a skinned vertex-based model that accurately represents a wide variety of body shapes in natural human poses.

The parameters of the model are learned from data including the

rest pose template,

blend weights,

pose-dependent blend shapes,

identity-dependent blend shapes,

and a regressor from vertices to joint locations.

Unlike previous models, the pose-dependent blend shapes are a linear function of the elements of the pose rotation matrices.

This simple formulation enables training the entire model from a relatively large number of aligned 3D meshes of different people in different poses.

We quantitatively evaluate variants of SMPL using linear or dual-quaternion blend skinning and show that both are more accurate than a Blend-SCAPE model trained on the same data.

We also extend SMPL to realistically model dynamic soft-tissue deformations. Because it is based on blend skinning,

SMPL is compatible with existing rendering engines and we make it available for research purposes.

SMPLは頂点数6890点のメッシュおよび23点の関節点により人物形状と姿勢を表現するモデルです。

このモデルは形状ベクトル β と姿勢ベクトル θ をパラメータとして持ち、これらのパラメータを変化させることにより人物の形状と姿勢を操作することができます。

各パラメータにおける人物形状および姿勢はモーションキャプチャシステムを用いて構築された人体メッシュデータセットを用いた学習により決定されます。

FYI