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ISCApad Archive  »  2018  »  ISCApad #235  »  Resources  »  Software  »  Bob signal-processing and machine learning toolbox (v.1.2..0)

ISCApad #235

Wednesday, January 10, 2018 by Chris Wellekens

5-3-3 Bob signal-processing and machine learning toolbox (v.1.2..0)

    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.

It is developed by the Biometrics Group at Idiap in  Switzerland.

    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. ).
    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

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