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CDnet 2014: An Expanded Change Detection Benchmark Dataset
Open accessAbstract
Change detection is one of the most important lowlevel 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 DetectionWorkshop 2014. We highlight strengths and weaknesses of these methods and identify remaining issues in change detection.
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Cited by
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Metadata
- Authors
- Wang, Y., Jodoin, P.-M., Porikli, F., Konrad, J., Benezeth, Y., & Ishwar, P.
- Venue
- 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
- Publisher
- IEEE
- Published
- 2014-06
- Pages
- 393-400
- OpenAlex
- W2101705628
- Cited by
- 882
- References
- 0
- FWCI
- 30.63
- Type
- conference paper
- Language
- en
- Open access
- green
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- Wang, Y., Jodoin, P.-M., Porikli, F., Konrad, J., Benezeth, Y., & Ishwar, P. (2014). CDnet 2014: An Expanded Change Detection Benchmark Dataset. 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops. https://doi.org/10.1109/cvprw.2014.126
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