02 · Edit M.S. Thesis · Texas A&M University · 2025

3DFilmPCA

Rigged 3D Gaussian Splatting for SMPL-driven pre-composite action control — real-time pose and shape editing of film-ready avatars.

Department of Visualization, Texas A&M University

3DFilmPCA rigs 3D Gaussians to SMPL for real-time pose and shape editing of film-ready avatars.

Abstract

Direct the avatar, in real time

Once a photorealistic avatar exists, an artist needs to direct it. 3DFilmPCA is a rigged 3D Gaussian Splatting system for SMPL-driven, pre-composite action control from monocular video.

Each 3D Gaussian is bound to a triangle on the SMPL mesh and transformed through a local-to-global parameterization, so posing the skeleton moves the splats coherently across frames. A binding-inheritance density strategy adds detail where it's needed, and an area-aware scaling rule keeps splats proportionate as body shape changes. A custom interactive viewer exposes per-joint rotations and PCA shape parameters with immediate visual feedback.

The system supports real-time pose and shape editing, motion transfer onto cinematic sequences, and free-viewpoint rendering for compositing. 3DFilmPCA is Module 2; the companion reconstruction method is GSDHuman.

Results

Avatars in motion

Editing

Shape & pose, live

Shape editing

PCA-based SMPL shape parameters are exposed as sliders — height, chest, waist, and more. Deformations reflect on the rigged Gaussian avatar in real time, retargeting the body to different builds while preserving appearance.

Pose editing

Joint-level control over the SMPL kinematic tree: select a joint and adjust its X/Y/Z rotation. The change updates the SMPL pose vector and drives the bound Gaussians via linear blend skinning, with immediate feedback.

Interactive viewer

One panel, full control

A custom real-time viewer ties the system together — reporting live metrics and Gaussian count, toggling splat and mesh views, and driving every edit from a single interface.

Compositing

Motion transfer & free-viewpoint

SMPL poses estimated from film clips are transferred onto the trained avatar; foreground segmentation and inpainting recover a clean background for compositing. The rigged Gaussians render from arbitrary angles with consistent appearance.

Contributions

What's new

Related

Builds on

Citation

BibTeX

@mastersthesis{hsiao2025avatars,
  title   = {Photorealistic Human Avatar Generation and Real-Time
             Pose Editing with Gaussian Splatting},
  author  = {Hsiao, Yi-Cheng},
  school  = {Texas A\&M University},
  year    = {2025},
  month   = aug,
  type    = {Master's thesis},
  url     = {https://nelson-hsiao-0101.github.io/3DFilmPCA/static/YI-CHENG-PRIMARY-2025.pdf}
}

Acknowledgments & funding

Texas A&M University Department of Visualization National Science Foundation

Graduate study was supported by a fellowship from Texas A&M University and research funding from the National Science Foundation.

I sincerely thank Xin Li for his guidance and insight throughout this thesis, and my committee members John Keyser and Ann McNamara for their valuable feedback.