The release 1.2.0 of the Bob signal-processing and machine learning toolbox is available .
    Bob provides both efficient implementations of several machine     learning algorithms as well as a framework to help researchers to     publish reproducible research.
   
   

   
    The previous release of Bob was providing:
    * image, video and audio IO interfaces such as jpg, avi, wav, 
    * database accessors such as FRGC, Labelled Face in the Wild, and many     others,
    *mage processing: Local Binary Patterns (LBPs), Gabor Jets,  SIFT,
    * machines  and trainers such as Support Vector Machines (SVMs), k-Means,     Gaussian Mixture Models (GMMs), Inter-Session Variability modeling     (ISV), Joint Factor Analysis (JFA), Probabilistic Linear     Discriminant Analysis (PLDA), Bayesian intra/extra (personal)     classifier,
   
    The new release of Bob has brought the following features and/or improvements, such as:
    * Unified implementation of Local Binary Patterns (LBPs),
    * Histograms of Oriented Gradients (HOG) implementation,
    * Total variability (i-vector) implementation,
    * Conjugate gradient based-implementation for logistic regression,
    * Improved multi-layer perceptrons implementation (Back-propagation can now be easily used in combination with any optimizer -- i.e     L-BFGS),
    * Pseudo-inverse-based method for Linear Discriminant Analysis,
    * Covariance-based method for Principal Component Analysis,
    * Whitening and within-class covariance normalization techniques,
    * Module for object detection and keypoint localization     (bob.visioner),
    * Module for audio processing including feature extraction such as LFCC and     MFCC,
    * Improved extensions (satellite packages), that now support both     Python and C++ code, within an easy to use framework,
    * Improved documentation and add new tutorials,
    * Support for Intel's MKL (in addition to ATLAS),
    * Extend supported platforms (Arch Linux).
   
    This release represents a major milestone in Bob with plenty of  functionality improvements (>640 commits in total) and plenty of bug fixes.
    • Sources and Documentation
    • Binary packages:
    •     Ubuntu: 10.04, 12.04, 12.10 and 13.04
    • For     Mac OSX: works with 10.6 (Snow Leopard), 10.7 (Lion) and 10.8     (Mountain Lion)
   
    For instructions on how to install pre-packaged version on Ubuntu or     OSX, consult our quick       installation instructions  (N.B. OS X macport has not yet been     upgraded. This will be done very soon. cf. https://trac.macports.org/ticket/39831 ).
   
   
    Best regards,
    Elie Khoury (on Behalf of the Biometric Group at Idiap lead by Sebastien Marcel)
   
     
     ---    

 Dr. Elie Khoury Post Doctorant Biometric Person Recognition Group 

IDIAP Research Institute (Switzerland) Tel : +41 27 721 77 23