Prativadibhayankaram S, van Luong H, Le TH, Kaup A (2018)
Publication Type: Journal article
Publication year: 2018
Book Volume: 4
Article Number: 90
Journal Issue: 7
In the context of video background-foreground separation, we propose a compressive online Robust Principal Component Analysis (RPCA) with optical flow that separates recursively a sequence of video frames into foreground (sparse) and background (low-rank) components. This separation method operates on a small set of measurements taken per frame, in contrast to conventional batch-based RPCA, which processes the full data. The proposed method also leverages multiple prior information by incorporating previously separated background and foreground frames in an n-`
APA:
Prativadibhayankaram, S., van Luong, H., Le, T.H., & Kaup, A. (2018). Compressive online video background-foreground separation using multiple prior information and optical flow. Journal of Imaging, 4(7). https://doi.org/10.3390/jimaging4070090
MLA:
Prativadibhayankaram, Srivatsa, et al. "Compressive online video background-foreground separation using multiple prior information and optical flow." Journal of Imaging 4.7 (2018).
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