Face Detection Toolbox (Scripts) Publisher's description
from Sebastien Paris
This toolbox provides some tools for faces detection/classification using Local Binary Patterns (and some variants) and Haar features
Faces detection toolbox v 0.2
This toolbox provides some tools for faces detection/classification using Local Binary Patterns (and some variants) and Haar features.
Face detection is performed by evaluating over multi-scans windows trained models with boosting approach
(such Adaboosting, FastAdaboosting and Gentleboosting) or with Fast SVM solvers.
The main objective of FDT is to deliver simple but efficient tools mainly written in C codes with a matlab interface and easy to modify.
This toolbox has been tested on Windows system and should also work for Linux plateform without any problem.
Please run "setup_fdt" to install, compile each mex-files and add fdtool directory in the matlab path.
Type "help mexme_fdt" for more compilation options.
Please open *.m or *.c files to read full description/instruction of each function and main references.
a) Play with "demo_detector_haar.m" or "demo_detector_hmblbp.m" for real-time face tracking.
For windows system, you can use the included VCAPG2 webcam grabber. Otherwise and for Linux system, you must have the IMAQ Toolbox (getsnapshot function).
b) View examples included in "train_cascade" for training a complete cascade with boosting algorithms (type: help train_cascade)
c) View examples included in "train_histoint_feat_boost" for training fast Histogram integral LBP + Fast linear SVM
(type: help train_histoint_feat_boost)
Please open "readme.txt" for details and references
System Requirements:MATLAB 7.8 (R2009a)
Program Release Status: New Release
Program Install Support: Install and Uninstall