SELFI3-D

SELFI3-D: Facial Mesh Reconstruction and Tattoo Visualization

SELFI3-D is a pipeline for facial mesh reconstruction and tattoo visualization from sparse input views. This project helps users visualize what they would look like with face tattoos before making permanent decisions.

Overview

Using a combination of gaussian splatting, poisson reconstruction, and texture mapping, SELFI3-D creates realistic 3D facial reconstructions from a small set of input images. The system then allows users to apply custom tattoo designs to their facial model with realistic texture mapping.

Features

3D facial reconstruction from sparse image views
High-quality texture mapping of facial features
Tattoo visualization on reconstructed face models
Realistic rendering with proper lighting and shading

Installation

Prerequisites

Python 3.8+
Required packages (install via pip):
```
pip install -r requirements.txt
```

Setup

Clone the repository:

git clone https://github.com/jameson-crate/SELFI3-D.git
cd SELFI3-D

Install dependencies:
```
pip install -r requirements.txt
```

Usage

Prepare your input images in the input/ directory

Run the reconstruction pipeline:

python reconstruct.py --input input/images/ --output output/mesh/

Apply a tattoo design:

python apply_tattoo.py --mesh output/mesh/face.obj --tattoo designs/tattoo.png --output output/final/

Team Members

Jameson Crate
Michelle Chen
Valerie Li
Akshaan Ahuja

Project Website

For more information, visit our project website.

License

This project is licensed under the MIT License - see the LICENSE file for details.