Real-time planar flow velocity measurements using an optical flow algorithm implemented on GPU
N. Gautier, J-L. Aider

TL;DR
This paper introduces a GPU-accelerated optical flow algorithm capable of real-time planar velocity measurements in experimental flows, enabling immediate flow analysis and control with accuracy comparable to traditional PIV methods.
Contribution
The paper presents a novel high-speed GPU implementation of optical flow for real-time flow velocity measurement, validated against PIV, with scalable architecture for higher resolutions and precision.
Findings
Real-time optical flow measurements match PIV accuracy.
System achieves high computation speed and scalability.
Flow features like recirculation dynamics are accurately captured.
Abstract
This paper presents a high speed implementation of an optical flow algorithm which computes planar velocity fields in an experimental flow. Real-time computation of the flow velocity field allows the experimentalist to have instantaneous access to quantitative features of the flow. This can be very useful in many situations: fast evaluation of the performances and characteristics of a new setup, design optimization, easier and faster parametric studies, etc. It can also be a valuable measurement tool for closed-loop flow control experiments where fast estimation of the state of the flow is needed. The algorithm is implemented on a Graphics Processing Unit (GPU). The accuracy of the computation is shown. Computation speed and scalability are highlighted along with guidelines for further improvements. The system architecture is flexible, scalable and can be adapted on the fly in order to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Vision and Imaging · Fluid Dynamics and Turbulent Flows · Advanced Image Processing Techniques
