{ "info": { "author": "Tiago de Freitas Pereira", "author_email": "tiago.pereira@idiap.ch", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Programming Language :: Python", "Topic :: Scientific/Engineering :: Artificial Intelligence" ], "description": ".. image:: https://gitlab.idiap.ch/biometric/bob.paper.CVPRW_2016/badges/master/build.svg?\n :target: https://gitlab.idiap.ch/biometric/bob.paper.CVPRW_2016/commits/master\n.. image:: http://img.shields.io/badge/docs-stable-yellow.png\n :target: http://pythonhosted.org/bob.paper.CVPRW_2016/index.html\n.. image:: https://img.shields.io/badge/github-master-0000c0.png\n :target: https://gitlab.idiap.ch/tiago.pereira/CVPRW_2016/tree/master\n.. image:: http://img.shields.io/pypi/v/bob.paper.CVPRW_2016.png\n :target: https://pypi.python.org/pypi/bob.paper.CVPRW_2016\n.. image:: https://img.shields.io/badge/original-data--files-a000a0.png\n :target: http://www.cbsr.ia.ac.cn/english/NIR-VIS-2.0-Database.html\n.. image:: https://img.shields.io/badge/original-data--files-a000a0.png\n :target: http://mmlab.ie.cuhk.edu.hk/archive/facesketch.html\n\n========================================================================\nHeterogeneous Face Recognition using Inter-Session Variability Modelling\n========================================================================\n\nThis package provides the source code to run the experiments published in the paper `Heterogeneous Face Recognition using Inter-Session Variability Modelling `_.\n\nIf you use this package and/or its results, please cite the following publications:\n\n1. The original paper with the counter-measure explained in details::\n\n @inproceedings{Pereira_CVPRW2016,\n author = {Pereira, Tiago de Freitas and Marcel, S{\\'{e}}bastien},\n keywords = {Face Recognition, Session Variability Modelling, Heterogeneous Face Recognition},\n month = jun,\n year = {2016},\n title = {Heterogeneous Face Recognition using Inter-Session Variability Modelling},\n journal = {IEEE Computer Society Workshop on Biometrics - CVPRW 2016},\n }\n\n\n2. Bob as the core framework used to run the experiments::\n\n @inproceedings{Anjos_ACMMM_2012,\n author = {A. Anjos AND L. El Shafey AND R. Wallace AND M. G\\\"unther AND C. McCool AND S. Marcel},\n title = {Bob: a free signal processing and machine learning toolbox for researchers},\n year = {2012},\n month = oct,\n booktitle = {20th ACM Conference on Multimedia Systems (ACMMM), Nara, Japan},\n publisher = {ACM Press},\n }\n\n\n\n\n\nRaw Data\n--------\n \nThis package does not provide the dataset used in the paper.\nThey must be downloaded separately from CUHK_CUFS (``_) and CBSR NIR-VIS-2.0 (``_).\n\n \n\nInstallation\n------------\n\n.. note:: \n\n If you are reading this page through our GitHub portal and not through PyPI,\n note **the development tip of the package may not be stable** or become\n unstable in a matter of moments.\n\n Go to `http://pypi.python.org/pypi/antispoofing.lbptop\n `_ to download the latest\n stable version of this package.\n\nThere are 2 options you can follow to get this package installed and\noperational on your computer: you can use automatic installers like `pip\n`_ (or `easy_install\n`_) or manually download, unpack and\nuse `zc.buildout `_ to create a\nvirtual work environment just for this package.\n\n\n\nUsing an automatic installer\n============================\n\nUsing ``pip`` is the easiest (shell commands are marked with a ``$`` signal)::\n\n $ pip install bob.paper.CVPRW_2016\n\nYou can also do the same with ``easy_install``::\n\n $ easy_install bob.paper.CVPRW_2016\n\nThis will download and install this package plus any other required\ndependencies. It will also verify if the version of Bob you have installed\nis compatible.\n\nThis scheme works well with virtual environments by `virtualenv\n`_ or if you have root access to your\nmachine. Otherwise, we recommend you use the next option.\n\nUsing ``zc.buildout``\n=====================\n\nDownload the latest version of this package from `PyPI\n`_ and unpack it in your\nworking area. The installation of the toolkit itself uses `buildout\n`_. You don't need to understand its inner workings\nto use this package. Here is a recipe to get you started::\n \n $ python bootstrap.py \n $ ./bin/buildout\n\nReproducibility\n---------------\nPlease, check our documentation in order to reproduce the results of the paper.\n\n \n \n.. _Bob: http://idiap.github.io/bob/ \n.. _virtualbox: http://www.virtualbox.org\n.. _bob_bio: https://pypi.python.org/pypi/bob.bio.gmm/", "description_content_type": null, "docs_url": "https://pythonhosted.org/bob.paper.CVPRW_2016/", "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://gitlab.idiap.ch/", "keywords": "bob", "license": "BSD", "maintainer": null, "maintainer_email": null, "name": "bob.paper.CVPRW_2016", "package_url": "https://pypi.org/project/bob.paper.CVPRW_2016/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/bob.paper.CVPRW_2016/", "project_urls": { "Download": "UNKNOWN", "Homepage": "http://gitlab.idiap.ch/" }, "release_url": "https://pypi.org/project/bob.paper.CVPRW_2016/1.0.2/", "requires_dist": null, "requires_python": null, "summary": "Running the experiments as given in paper: \"Heterogeneous Face Recognition using Inter-Session Variability Modelling\".", "version": "1.0.2" }, "last_serial": 2355346, "releases": { "1.0.0": [ { "comment_text": "", "digests": { "md5": "55c0835fcfc07e26144730218ae39005", "sha256": "2deee8c8aa8966a0d0af1d78cc9720d600dfb14540c8edf473c97cfd4b46803b" }, "downloads": -1, "filename": "bob.paper.CVPRW_2016-1.0.0.zip", "has_sig": false, "md5_digest": "55c0835fcfc07e26144730218ae39005", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 40453, "upload_time": "2016-06-23T13:40:46", "url": "https://files.pythonhosted.org/packages/1d/10/aff5bc77cfe3e1670ed2635f0a8edc7ee10cd4e80d33e9366eefad1a63f4/bob.paper.CVPRW_2016-1.0.0.zip" } ], "1.0.0b0": [ { "comment_text": "", "digests": { "md5": "99af8399b4ecec73ec1a46778065d6c2", "sha256": "2d622a30b1ad7879fa441fb4bb4e59537933ff93af9b61e14b4a753f96b03d71" }, "downloads": -1, "filename": "bob.paper.CVPRW_2016-1.0.0b0.zip", "has_sig": false, "md5_digest": "99af8399b4ecec73ec1a46778065d6c2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 40692, "upload_time": "2016-05-01T14:33:02", "url": "https://files.pythonhosted.org/packages/46/d5/8a4340c5e82cb070c6c7a5bbb4f6097dbc7022aeb7748ccfcb3d72ee9d6a/bob.paper.CVPRW_2016-1.0.0b0.zip" } ], "1.0.0b1": [ { "comment_text": "", "digests": { "md5": "12c17366dccfccc856b92c21283ad8ca", "sha256": "563287bd61264ec5112b5e6e0094fd07c9c41ffd956f3c2f1328bf1e2c67660f" }, "downloads": -1, "filename": "bob.paper.CVPRW_2016-1.0.0b1.zip", "has_sig": false, "md5_digest": "12c17366dccfccc856b92c21283ad8ca", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 40551, "upload_time": "2016-05-01T14:47:27", "url": "https://files.pythonhosted.org/packages/8e/85/7490809e468b27c4f891c57bd4ab5085b900dfa4d2ea50fd013d90709096/bob.paper.CVPRW_2016-1.0.0b1.zip" } ], "1.0.1": [], "1.0.2": [ { "comment_text": "", "digests": { "md5": "10a81c042cf58a9a593412260763981d", "sha256": "7e5c48ea1fad9e0d2d822c5ac3c9ad36a25dcaff354e3bfb079d5d92bae8d556" }, "downloads": -1, "filename": "bob.paper.CVPRW_2016-1.0.2.zip", "has_sig": false, "md5_digest": "10a81c042cf58a9a593412260763981d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 40452, "upload_time": "2016-06-23T15:41:49", "url": "https://files.pythonhosted.org/packages/d9/c3/1ba333aba7e3c4e7ce6b053240cf44210eff425ff51d1b876c5967b2ac24/bob.paper.CVPRW_2016-1.0.2.zip" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "10a81c042cf58a9a593412260763981d", "sha256": "7e5c48ea1fad9e0d2d822c5ac3c9ad36a25dcaff354e3bfb079d5d92bae8d556" }, "downloads": -1, "filename": "bob.paper.CVPRW_2016-1.0.2.zip", "has_sig": false, "md5_digest": "10a81c042cf58a9a593412260763981d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 40452, "upload_time": "2016-06-23T15:41:49", "url": "https://files.pythonhosted.org/packages/d9/c3/1ba333aba7e3c4e7ce6b053240cf44210eff425ff51d1b876c5967b2ac24/bob.paper.CVPRW_2016-1.0.2.zip" } ] }