# Synthetic Human Model Dataset for Skeleton Driven Non-rigid Motion Tracking and 3D Reconstruction

## TL;DR

This paper presents a synthetic dataset designed for evaluating non-rigid 3D human reconstruction using RGB-D cameras, including detailed ground truth data for geometry and skeletons across multiple motion sequences.

## Contribution

The authors introduce a comprehensive synthetic dataset with ground truth geometry, skeletons, and skinning weights for non-rigid human motion analysis.

## Key findings

- Provides detailed ground truth data for 7 motion sequences
- Enables evaluation of non-rigid 3D human reconstruction methods
- Facilitates benchmarking with synthetic, controlled data

## Abstract

We introduce a synthetic dataset for evaluating non-rigid 3D human reconstruction based on conventional RGB-D cameras. The dataset consist of seven motion sequences of a single human model. For each motion sequence per-frame ground truth geometry and ground truth skeleton are given. The dataset also contains skinning weights of the human model. More information about the dataset can be found at: https://research.csiro.au/robotics/our-work/databases/synthetic-human-model-dataset/