Recovering estimates of fluid flow from image sequence data

Richard P. Wildes, Michael J. Amabile, Ann Marie Lanzillotto, Tzong Shyng Leu

研究成果: Article同行評審

67 引文 斯高帕斯(Scopus)

摘要

This paper presents an approach to measuring fluid flow from image sequences. The approach centers around a motion-recovery algorithm that is based on principles from fluid mechanics: The algorithm is constrained so that recovered flows observe conservation of mass as well as physically motivated boundary conditions. Empirical results from application of the algorithm to transmittance imagery of fluid flows, where the fluids contained a contrast medium, are presented. In these experiments, the algorithm recovered accurate and precise estimates of the flow. The significance of this work is twofold. First, from a theoretical point of view it is shown how information derived from the physical behavior of fluids can be used to motivate a flow-recovery algorithm. Second, from an applications point of view the developed algorithm can be used to augment the tools that are available for the measurement of fluid dynamics; other imaged flows that observe compatible constraints might benefit in a similar fashion.

原文English
頁(從 - 到)246-266
頁數21
期刊Computer Vision and Image Understanding
80
發行號2
DOIs
出版狀態Published - 2000 11月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 訊號處理
  • 電腦視覺和模式識別

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