# Model-based Outdoor Performance Capture

arXiv: https://arxiv.org/abs/1610.06740 · HTML: https://mlsanity.com/paper/1610.06740/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Oct 2016.

## Built on by (most cited first, 13 of 13)

- [InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions](https://mlsanity.com/paper/2304.05684/) (2023)
- [Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On](https://mlsanity.com/paper/2105.06462/) (2021)
- [LiDAR-aid Inertial Poser: Large-scale Human Motion Capture by Sparse Inertial and LiDAR Sensors](https://mlsanity.com/paper/2205.15410/) (2022)
- [Generalizable Human Gaussians for Sparse View Synthesis](https://mlsanity.com/paper/2407.12777/) (2024)
- [ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References](https://mlsanity.com/paper/2103.06747/) (2021)
- [PERGAMO: Personalized 3D Garments from Monocular Video](https://mlsanity.com/paper/2210.15040/) (2022)
- [Drivable Avatar Clothing: Faithful Full-Body Telepresence with Dynamic Clothing Driven by Sparse RGB-D Input](https://mlsanity.com/paper/2310.05917/) (2023)
- [LiveHPS: LiDAR-based Scene-level Human Pose and Shape Estimation in Free Environment](https://mlsanity.com/paper/2402.17171/) (2024)
- [HybridCap: Inertia-aid Monocular Capture of Challenging Human Motions](https://mlsanity.com/paper/2203.09287/) (2022)
- [Detailed Avatar Recovery from Single Image](https://mlsanity.com/paper/2108.02931/) (2021)
- [Real-time Free-view Human Rendering from Sparse-view RGB Videos using Double Unprojected Textures](https://mlsanity.com/paper/2412.13183/) (2024)
- [LiveHPS++: Robust and Coherent Motion Capture in Dynamic Free Environment](https://mlsanity.com/paper/2407.09833/) (2024)
- [Disambiguating Monocular Reconstruction of 3D Clothed Human with Spatial-Temporal Transformer](https://mlsanity.com/paper/2410.16337/) (2024)

## Abstract (arXiv)

We propose a new model-based method to accurately reconstruct human performances captured outdoors in a multi-camera setup. Starting from a template of the actor model, we introduce a new unified implicit representation for both, articulated skeleton tracking and nonrigid surface shape refinement. Our method fits the template to unsegmented video frames in two stages - first, the coarse skeletal pose is estimated, and subsequently non-rigid surface shape and body pose are jointly refined. Particularly for surface shape refinement we propose a new combination of 3D Gaussians designed to align the projected model with likely silhouette contours without explicit segmentation or edge detection. We obtain reconstructions of much higher quality in outdoor settings than existing methods, and show that we are on par with state-of-the-art methods on indoor scenes for which they were designed