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- Title
A FRAMEWORK FOR FLUID MOTION ESTIMATION USING A CONSTRAINT-BASED REFINEMENT APPROACH.
- Authors
Doshi, Hirak; Nori, Uday Kiran
- Abstract
Physics-based optical flow models have been successful in capturing the deformities in fluid motion arising from digital imagery. However, a common theoretical framework analyzing several physics-based models is missing. In this regard, we formulate a general framework for fluid motion estimation using a constraint-based refinement approach. We demonstrate that for a particular choice of constraint, our results closely approximate the classical continuity equation-based method for fluid flow. This closeness is theoretically justified by augmented Lagrangian method in a novel way. The convergence of Uzawa iterates is shown using a modified bounded constraint algorithm. The mathematical well-posedness is studied in a Hilbert space setting. Further, we observe a surprising connection to the Cauchy-Riemann operator that diagonalizes the system leading to a diffusive phenomenon involving the divergence and the curl of the flow. Several numerical experiments are performed and the results are shown on different datasets. Additionally, we demonstrate that a flow-driven refinement process involving the curl of the flow outperforms the classical physics-based optical flow method without any additional assumptions on the image data.
- Subjects
FLUID dynamics; IMAGE processing; COMPUTER algorithms; OPTICAL flow; HILBERT space
- Publication
Machine Graphics & Vision, 2023, Vol 32, Issue 3/4, p17
- ISSN
1230-0535
- Publication type
Article
- DOI
10.22630/MGV.2023.32.3.2