Foreground background segmentation algorithms attempt to separate interesting or changing regions from the background in video sequences. Foreground detection is obviously more difficult when the camera viewpoint changes dynamically, such as when the camera undergoes a panning or tilting motion. In this paper, we propose an edge based foreground background estimation method, which can automatically detect and compensate for camera viewpoint changes. We will show that this method significantly outperforms state-of-the-art algorithms for the panning sequences in the ChangeDetection.NET 2014 dataset, while still performing well in the other categories.
CITATION STYLE
Allebosch, G., Deboeverie, F., Veelaert, P., & Philips, W. (2015). EFIC: Edge based foreground background segmentation and interior classification for dynamic camera viewpoints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9386, pp. 130–141). Springer Verlag. https://doi.org/10.1007/978-3-319-25903-1_12
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