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Publications about 'Dataset'
Thesis
  1. B. Laugraud. Motion-aware temporal median filtering for robust background estimation. PhD thesis, University of Liège, Belgium, March 2020. Keyword(s): Background estimation, Background initialization, Background generation, Motion detection, Background subtraction, Optical flow, Semantic segmentation, Scene parsing, Median filtering, SBI dataset, SBMnet dataset, LaBGen, LaBGen-P, LaBGen-OF, LaBGen-P-Semantic, Computer vision, Image processing. [bibtex-entry]


Articles in journal or book chapters
  1. 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. [bibtex-entry]


Conference articles
  1. M. Fonder and M. Van Droogenbroeck. Mid-Air: A multi-modal dataset for extremely low altitude drone flights. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), UAVision, Long Beach, California, USA, pages 553-562, June 2019. Keyword(s): UAV, Dataset, Mid-Air, Positioning, Benchmark, Drone, Artificial Intelligence, Deep learning. [bibtex-entry]


  2. 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. [bibtex-entry]


  3. S. Azrour, S. Piérard, and M. Van Droogenbroeck. Improving pose estimation by building dedicated datasets and using orientation. In IET Workshop on Human Motion Analysis for Healthcare Applications, London, United Kingdom, May 2016. Keyword(s): Pose estimation, Human, Depth camera, 3D camera, Orientation. [bibtex-entry]


  4. J. Osmalskyj, S. Piérard, M. Van Droogenbroeck, and J.-J. Embrechts. Efficient database pruning for large-scale cover song recognition. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), Vancouver, Canada, May 2013. Keyword(s): Song, Recognition, Million Song Dataset, Music Information Retrieval, Chromas, Rejectors, Cover Songs. [bibtex-entry]



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Last modified: Tue Jul 14 12:42:55 2020