Abstract : Change detection is one of the most important low-level tasks in video analytics. In 2012, we introduced the changedetection.net (CDnet) benchmark, a video dataset devoted to the evalaution of change and motion detection approaches. Here, we present the latest release of the CDnet dataset, which includes 22 additional videos (~70,000 pixel-wise annotated frames) spanning 5 new categories that incorporate challenges encountered in many surveillance settings. We describe these categories in detail and provide an overview of the results of more than a dozen methods submitted to the IEEE Change Detection Workshop 2014. We highlight strengths and weaknesses of these methods and identify remaining issues in change detection.
Type de document :
Communication dans un congrès
IEEE CVPR Change Detection workshop, Jun 2014, United States. 8 p., 2014
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01018757
Contributeur : Yannick Benezeth
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Soumis le : vendredi 4 juillet 2014 - 22:31:36
Dernière modification le : mercredi 12 septembre 2018 - 01:27:19
Document(s) archivé(s) le : samedi 4 octobre 2014 - 13:06:19
Yi Wang, Pierre-Marc Jodoin, Fatih Porikli, Janusz Konrad, Yannick Benezeth, et al.. CDnet 2014: An Expanded Change Detection Benchmark Dataset. IEEE CVPR Change Detection workshop, Jun 2014, United States. 8 p., 2014. 〈hal-01018757〉
