TY - JOUR
T1 - Recovering estimates of fluid flow from image sequence data
AU - Wildes, Richard P.
AU - Amabile, Michael J.
AU - Lanzillotto, Ann Marie
AU - Leu, Tzong Shyng
N1 - Funding Information:
1 The research that is described in this paper was funded by DARPA/ETO under Contract DABT63-95-C-0057.
PY - 2000/11
Y1 - 2000/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0034321082&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034321082&partnerID=8YFLogxK
U2 - 10.1006/cviu.2000.0874
DO - 10.1006/cviu.2000.0874
M3 - Article
AN - SCOPUS:0034321082
SN - 1077-3142
VL - 80
SP - 246
EP - 266
JO - Computer Vision and Image Understanding
JF - Computer Vision and Image Understanding
IS - 2
ER -