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Asynchronous Semantic Background Subtraction

Montefiore Institute, University of Liège, Quartier Polytech 1, Allée de la Découverte 10, 4000 Liège, Belgium
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J. Imaging 2020, 6(6), 50; https://doi.org/10.3390/jimaging6060050
Received: 30 April 2020 / Revised: 9 June 2020 / Accepted: 13 June 2020 / Published: 18 June 2020
The method of Semantic Background Subtraction (SBS), which combines semantic segmentation and background subtraction, has recently emerged for the task of segmenting moving objects in video sequences. While SBS has been shown to improve background subtraction, a major difficulty is that it combines two streams generated at different frame rates. This results in SBS operating at the slowest frame rate of the two streams, usually being the one of the semantic segmentation algorithm. We present a method, referred to as “Asynchronous Semantic Background Subtraction” (ASBS), able to combine a semantic segmentation algorithm with any background subtraction algorithm asynchronously. It achieves performances close to that of SBS while operating at the fastest possible frame rate, being the one of the background subtraction algorithm. Our method consists in analyzing the temporal evolution of pixel features to possibly replicate the decisions previously enforced by semantics when no semantic information is computed. We showcase ASBS with several background subtraction algorithms and also add a feedback mechanism that feeds the background model of the background subtraction algorithm to upgrade its updating strategy and, consequently, enhance the decision. Experiments show that we systematically improve the performance, even when the semantic stream has a much slower frame rate than the frame rate of the background subtraction algorithm. In addition, we establish that, with the help of ASBS, a real-time background subtraction algorithm, such as ViBe, stays real time and competes with some of the best non-real-time unsupervised background subtraction algorithms such as SuBSENSE. View Full-Text
Keywords: background subtraction; motion detection; scene labeling; semantic segmentation; video processing background subtraction; motion detection; scene labeling; semantic segmentation; video processing
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MDPI and ACS Style

Cioppa, A.; Braham, M.; Van Droogenbroeck, M. Asynchronous Semantic Background Subtraction. J. Imaging 2020, 6, 50. https://doi.org/10.3390/jimaging6060050

AMA Style

Cioppa A, Braham M, Van Droogenbroeck M. Asynchronous Semantic Background Subtraction. Journal of Imaging. 2020; 6(6):50. https://doi.org/10.3390/jimaging6060050

Chicago/Turabian Style

Cioppa, Anthony, Marc Braham, and Marc Van Droogenbroeck. 2020. "Asynchronous Semantic Background Subtraction" Journal of Imaging 6, no. 6: 50. https://doi.org/10.3390/jimaging6060050

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