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• W2564871695 abstract "It is important to extract a clear background for computer vision and augmented reality. Generally, background extraction assumes the existence of a clean background shot through the input sequence, but realistically, situations may violate this assumption such as highway traffic videos. Therefore, our probabilistic model-based method formulates fusion of candidate background patches of the input sequence as a random walk problem and seeks a globally optimal solution based on their temporal and spatial relationship. Furthermore, we also design two quality measures to consider spatial and temporal coherence and contrast distinctness among pixels as background selection basis. A static background should have high temporal coherence among frames, and thus, we improve our fusion precision with a temporal contrast filter and an optical-flow-based motionless patch extractor. Experiments demonstrate that our algorithm can successfully extract artifact-free background images with low computational cost while comparing to state-of-the-art algorithms." @default.
• W2564871695 created "2017-01-06" @default.
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• W2564871695 date "2018-01-01" @default.
• W2564871695 modified "2023-10-17" @default.
• W2564871695 title "Background Extraction Using Random Walk Image Fusion" @default.
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• W2564871695 doi "https://doi.org/10.1109/tcyb.2016.2640288" @default.
• W2564871695 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28026799" @default.
• W2564871695 hasPublicationYear "2018" @default.
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