https://github.com/basilfx/course-face3d

Implementation of a prototype 3D Face recognition system
https://github.com/basilfx/course-face3d

Last synced: about 1 year ago
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Implementation of a prototype 3D Face recognition system

• Host: GitHub
• URL: https://github.com/basilfx/course-face3d
• Owner: basilfx
• License: mit
• Created: 2012-12-10T21:52:27.000Z (over 13 years ago)
• Default Branch: master
• Last Pushed: 2012-12-10T21:52:38.000Z (over 13 years ago)
• Last Synced: 2025-03-24T17:12:14.563Z (about 1 year ago)
• Language: Python
• Size: 105 KB
• Stars: 22
• Watchers: 8
• Forks: 9
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Face3D

Prototype system for 3D Face Recognition built by Bas Stottelaar and Jeroen Senden for the course Introduction to Biometrics. Written in Python, applicable to the FRGC 3D data set.

## Features

The following algorithms have been implemented:

### Normalization

* Smoothing

* Interpolation

* Cropping

* Zooming

* Key point extraction

* Rotation

### Feature extraction

Histogram based, as proposed by Zhou et al. See http://www.3dface.org/files/papers/zhou-EG08-histogram-face-rec.pdf for more information.

### Distance Metrics

* Method 0: Euclidean Distance with threshold 0.9

* Method 1: City Block Distance with threshold 0.9

* Method 2: Sample Correlation Coefficient with threshold 0.9

## Installation

The following dependencies are expected to be on your system

* Python 2.7 (version 2.6 should work)

* NumPy 1.6

* SciPy 0.11

* Matplotlib 1.2

* SciKit-learn 0.12

In case of missing dependencies, they can be installed via the Python Packet Manager, via the command `pip install `. 

## Quick Start

A few examples to get started:

* `python Face3D.py --enroll /path/to/abs/files --auto-id` — Enrolls all files in the folder and determines person identification based on filename.

* `python Face3D.py --authenticate /path/to/file.abs` — Authenticate given file against the enrolled images. Will output the matches with scores.

* `python Face3D.py --reevaluate --parameters N=48,K=12` — Reevaluate the data set with the given parameters. Does not save data, but you could visualize something with this data.

## Usage

Face3D is a commandline only application. Start a terminal and navigate to this directory where Face3D is extracted. Start the application with the command `python Face3D.py`.

### General

* `python Face3D.py --help` — Show help.

* `python Face3D.py --parameters` — Comma seperated key-value parameters for the algorithms. Defaults (and only parameters supported) are `N=67,K=12`.

* `python Face3D.py --database` — Specify the Face3D Database to work on. Default is `database.db`. You need to specify this option each time if you would like to use another database for operations below.

### Face management

* `python Face3D.py --enroll  --person-id |--auto-id` — Enroll a single file or a complete directory to the Face3D Database. Multiple threads will be spawned in case of multiple files. You have to specify a person ID. In case of auto ID, it will be derrived from the `*.abs` filename (xxxxxd123.abs). This process can take up to 15 minutes for 350+ faces on a Intel Core i7. If a face has already been enrolled, it will notify the user. Simply delete the database file to start over.

* `python Face3D.py --authenticate ` — Match a given face to a face in the database.

* `python Face3D.py --reevaluate` — Reevaluate the faces with another set of parameters. Works only for feature extraction and other calculations after feature extraction. This comes in handy when evaluating different parameters.

### Visualization & Statistics

* `python Face3D.py --depth-map  [--with-key-points]` — Write a 3D depth map of enrolled faces to a PDF file, with or without key points.

* `python Face3D.py --feature-map ` — Write a feature map of enrolled faces to a PDF file. 

* `python Face3D.py --similarity-matrix ` — Write a similarity matrix to a HTML file.

* `python Face3D.py --roc-curve ` — Write a ROC curve to a HTML file.

## Source code

The main application logic is defined in `Face3D.py`. The rest of the code is stored in the folder `face3d/`.

One important file is `face3d/algorithms.py`. Here are all the algorithms programmed that are used for smoothing, interpolating, finding key points, cropping, feature extracting. Dependencies are `face3d/absfile.py` and `face3d/face.py`. The first reads `*.abs` files into memory and the second one is a wrapper for the data and handles views and compression. 

On of the two files left is `face3d/database.py`, a wrapper for an SQLite3 database file. It reads and writes faces and features. Last but not least is `face3d/utils.py` as a place for common used methods.

## Licence

See the LICENCE file.