Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Basic tools for running spoofing or presentation attack detection (PAD) experiments

Vein biometrics recognition baselines

Bob access API for Fisher's Iris Flower Dataset

Experiment Evaluation Metrics for Bob

Software package to reproduce "Spoofing Deep Face Recognition with Custom Flexible Masks" published on BTAS 2018

U-NET based feature extractor for text-independent speaker verification

A collection of Matlab/GNU Octave functions for robot programming-by-demonstration that combine statistical learning, dynamical systems and optimal control.

Helps projects building Bob/Python C++ extensions

Implements tools for spoofing or presentation attack detection in face biometrics.

DRIVE Database Access API for Bob

CASIA NIR-VIS 2.0 Face Database API files for Bob

Source code to rerun experiments for the book chapter "Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey" in the 2016 Springer book "Face Recognition Across the Imaging Spectrum"

Example code that can be inserted in a new BEAT instance

A programming-by-demonstration C++ library combining statistical learning, dynamical systems and optimal control.

CPqD Biometric Database (BioCPqD, Phase 1)