Home
Students - Teaching
Research
Publications People Links

BACK TO INDEX

Publications of year 2017
Articles in journal or book chapters
  1. C. Gomez Gonzalez, O. Wertz, O. Absil, V. Christiaens, D. Defrere, D. Mawet, J. Milli, P.-A. Absil, M. Van Droogenbroeck, F. Cantalloube, P. Hinz, A. Skemer, M. Karlsson, and J. Surdej. VIP: Vortex Image Processing package for high-contrast direct imaging. The Astronomical Journal, 154(1):7:1-7:12, July 2017. Keyword(s): Exoplanet, High-contrast imaging, Vortex, VIP.
    @article{Gomez2017VIP,
    title = {{VIP}: {V}ortex {I}mage {P}rocessing package for high-contrast direct imaging},
    author = {C. Gomez Gonzalez and O. Wertz and O. Absil and V. Christiaens and D. Defrere and D. Mawet and J. Milli and P.-A. Absil and M. {Van Droogenbroeck} and F. Cantalloube and P. Hinz and A. Skemer and M. Karlsson and J. Surdej},
    journal = {The Astronomical Journal},
    volume = {154},
    number = {1},
    pages = {7:1-7:12},
    month = {July},
    year = {2017},
    keywords = {Exoplanet, High-contrast imaging, Vortex, VIP},
    doi = {10.3847/1538-3881/aa73d7},
    url = {http://hdl.handle.net/2268/212229},
    pdf = {http://orbi.ulg.ac.be/bitstream/2268/212229/1/vip_paper.pdf} 
    }
    


  2. P. Latour and M. Van Droogenbroeck. The LNQ25 and ELN PVT Metrics Exhibit a Good Sensitivity to Sleep Deprivation and are Independent from the Subject. Sleep Medicine, 40:178-179, December 2017. Keyword(s): PVT metrics, Metrics, Drowsiness, Automatic alertness monitoring, Fatigue management.
    @article{Latour2017TheLNQ25,
    title = {The {LNQ25} and {ELN PVT} Metrics Exhibit a Good Sensitivity to Sleep Deprivation and are Independent from the Subject},
    author = {P. Latour and M. {Van Droogenbroeck}},
    journal = {Sleep Medicine},
    volume = {40},
    pages = {178-179},
    year = {2017},
    month = {December},
    keywords = {PVT metrics, Metrics, Drowsiness, Automatic alertness monitoring, Fatigue management},
    doi = {10.1016/j.sleep.2017.11.523},
    url = {http://hdl.handle.net/2268/214824} 
    }
    


  3. B. Laugraud, S. Piérard, and M. Van Droogenbroeck. LaBGen: A Method Based on Motion Detection for Generating the Background of a Scene. Pattern Recognition Letters, 96:12-21, 2017. Keyword(s): LaBGen, Background initialization, Background generation, Background subtraction, SBMI dataset, SBMC contest.
    @article{Laugraud2017LaBGen,
    title = {{LaBGen}: A Method Based on Motion Detection for Generating the Background of a Scene},
    author = {B. Laugraud and S. Pi{\'e}rard and M. {Van Droogenbroeck}},
    journal = {Pattern Recognition Letters},
    publisher = {Elsevier},
    volume = {96},
    year = {2017},
    pages = {12-21},
    year = {2017},
    keywords = {LaBGen, Background initialization, Background generation, Background subtraction, SBMI dataset, SBMC contest},
    doi = {10.1016/j.patrec.2016.11.022},
    url = {http://hdl.handle.net/2268/203572} 
    }
    


Conference articles
  1. S. Azrour, S. Piérard, P. Geurts, and M. Van Droogenbroeck. A two-step methodology for human pose estimation increasing the accuracy and reducing the amount of learning samples dramatically. In Advanced Concepts for Intelligent Vision Systems (ACIVS), volume 10617 of Lecture Notes in Computer Science, pages 3-14, 2017. Keyword(s): Pose estimation, Orientation estimation.
    @inproceedings{Azrour2017ATwoStep,
    title = {A two-step methodology for human pose estimation increasing the accuracy and reducing the amount of learning samples dramatically},
    author = {S. Azrour and S. Pi{\'e}rard and P. Geurts and M. {Van Droogenbroeck}},
    booktitle = {Advanced Concepts for Intelligent Vision Systems (ACIVS)},
    series = {Lecture Notes in Computer Science},
    volume = {10617},
    pages = {3-14},
    year = {2017},
    keywords = {Pose estimation, Orientation estimation},
    doi = {10.1007/978-3-319-70353-4_1},
    url = {http://hdl.handle.net/2268/214238},
    pdf = {http://orbi.ulg.ac.be/bitstream/2268/214238/1/Azrour2017ATwoStep.pdf} 
    }
    


  2. M. Braham, S. Piérard, and M. Van Droogenbroeck. Semantic Background Subtraction. In IEEE International Conference on Image Processing, Beijing, China, pages 4552-4556, September 2017. Keyword(s): Background subtraction, Change detection, Semantic segmentation, Scene labeling, Scene parsing, Classification, Machine learning, Deep learning, CDNet 2014.
    @inproceedings{Braham2017Semantic,
    title = {Semantic Background Subtraction},
    author = {M. Braham and S. Pi\'erard and M. {Van Droogenbroeck}},
    booktitle = {IEEE International Conference on Image Processing},
    year = {2017},
    month = {September},
    pages = {4552-4556},
    address = {Beijing, China},
    keywords = {Background subtraction, Change detection, Semantic segmentation, Scene labeling, Scene parsing, Classification, Machine learning, Deep learning, CDNet 2014},
    doi = {10.1109/ICIP.2017.8297144},
    url = {http://dx.doi.org/10.1109/ICIP.2017.8297144},
    url = {http://www.telecom.ulg.ac.be/publi/publications/braham/Braham2017Semantic},
    pdf = {http://orbi.ulg.ac.be/bitstream/2268/213419/1/Braham2017Semantic.pdf} 
    }
    


  3. P. Latour and M. Van Droogenbroeck. New PVT Metrics with Improved Sensitivity to Sleep Loss: Analysis from Short to Long Time Intervals. In Managing Fatigue, San Diego, California, USA, March 2017. Keyword(s): PVT metrics, Fatigue, Sleep, Sleep deprivation, Drowsiness, Sleepiness.
    @inproceedings{Latour2017NewPVTMetrics,
    title = {New {PVT} Metrics with Improved Sensitivity to Sleep Loss: Analysis from Short to Long Time Intervals},
    author = {P. Latour and M. {Van Droogenbroeck}},
    booktitle = {Managing Fatigue},
    year = {2017},
    month = Mar,
    address = {San Diego, California, USA},
    keywords = {PVT metrics, Fatigue, Sleep, Sleep deprivation, Drowsiness, Sleepiness},
    url = {http://hdl.handle.net/2268/203874} 
    }
    


  4. B. Laugraud and M. Van Droogenbroeck. Is a Memoryless Motion Detection Truly Relevant for Background Generation with LaBGen?. In Advanced Concepts for Intelligent Vision Systems (ACIVS), volume 10617 of Lecture Notes in Computer Science, pages 443-454, 2017. Keyword(s): Background generation, Background initialization, Background subtraction, Optical flow, Motion detection, Median filter, SBI dataset, SBMnet dataset, LaBGen, LaBGen-OF.
    @inproceedings{Laugraud2017IsAMemoryless,
    title = {Is a Memoryless Motion Detection Truly Relevant for Background Generation with {LaBGen}?},
    author = {B. Laugraud and M. {Van Droogenbroeck}},
    booktitle = {Advanced Concepts for Intelligent Vision Systems (ACIVS)},
    series = {Lecture Notes in Computer Science},
    volume = {10617},
    pages = {443-454},
    year = {2017},
    keywords = {Background generation, Background initialization, Background subtraction, Optical flow, Motion detection, Median filter, SBI dataset, SBMnet dataset, LaBGen, LaBGen-OF},
    doi = {10.1007/978-3-319-70353-4_38},
    pdf = {http://orbi.ulg.ac.be/bitstream/2268/213147/1/Laugraud2017IsAMemoryless.pdf},
    url = {http://hdl.handle.net/2268/213147} 
    }
    



BACK TO INDEX




Disclaimer:

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.




Last modified: Fri Oct 2 15:41:54 2020