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• W2000305870 abstract "Despite recent advances, the extraction of optical flow with large displacements is still challenging for state-of the-art methods. The approaches that are the most successful at handling large displacements blend sparse correspondences from a matching algorithm with an optimization that refines the optical flow. We follow the scheme of Deep-Flow [33]. We first extract sparse pixel correspondences by means of a matching procedure and then apply a variational approach to obtain a refined optical flow. In our approach, coined 'Sparse Flow', the novelty lies in the matching. This uses an efficient sparse decomposition of a pixel's surrounding patch as a linear sum of those found around candidate corresponding pixels. As matching pixel the one dominating the decomposition is chosen. The pixel pairs matching in both directions, i.e. in a forward-backward fashion, are used as guiding points in the variational approach. Sparse-Flow is competitive on standard optical flow benchmarks with large displacements, while showing excellent performance for small and medium displacements. Moreover, it is fast in comparison to methods with a similar performance." @default.
• W2000305870 created "2016-06-24" @default.
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• W2000305870 date "2015-01-01" @default.
• W2000305870 modified "2023-09-26" @default.
• W2000305870 title "Sparse Flow: Sparse Matching for Small to Large Displacement Optical Flow" @default.
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• W2000305870 doi "https://doi.org/10.1109/wacv.2015.151" @default.
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