Welcome to Our Community Dr. Sidaard Gunasekaran, Ph.D., University of Dayton
Research Subcategory

Event-Camera Velocimetry and Algorithm Development

Flow Diagnostics and Event-Based Sensing / Event-Camera Velocimetry and Algorithm Development

Research in this area develops event-based cameras into serious tools for experimental fluid mechanics rather than treating them as a novelty in machine vision. Unlike conventional imaging systems that record full frames at fixed time intervals, event cameras register changes in intensity asynchronously, making them especially attractive for flows with fast transients, sparse motion cues, or strong local gradients. The work spans particle event velocimetry, weighted tracking, Kalman-filter-based tracking, motion-compensation methods, simulator-based benchmarking, and sensitivity analysis across wing, wake, and cavity flows. Taken together, the studies show how event-driven sensing can recover meaningful velocity fields while preserving the experimental simplicity that makes planar diagnostics practical in the laboratory.

Infographic

Research infographic

NotebookLM-generated infographic and video assets for this research subcategory. Click any image to open the full-size file, or play videos directly on the page.

A New View on Fluid Flow
Neuromorphic Fluid Dynamics Research Overview infographic
Neuromorphic Fluid Dynamics Research Overview
Contributors

Students who contributed to this work

Students connected to the publications and projects represented on this page.

Publications

Research publications in this area

Publication entries include citation details and student contributors where available.

Event-Based Velocimetry in Additive-Manufacturing Flowfields

Students

Student contributors are listed where available.

Citation
  • Event-Based Velocimetry in Additive-Manufacturing Flowfields. 2026.

Toward Event-Based Noise-Robust High Density Particle Velocimetry

Students
Andrew KillianMichael Mongin
Citation
  • AlSattam, Osama A., Michael P. Mongin, Andrew Killian, Sidaard Gunasekaran, and Keigo Hirakawa. "Toward Event-Based Noise-Robust High Density Particle Velocimetry." In AIAA SCITECH 2024 Forum, p. 2663. 2024. https://doi.org/10.2514/6.2024-2663

Comparison of Event-Based Alogrithms for Experimental Two-Dimensional, Two-Component Velocimetry

Students
Michael Mongin
Citation
  • Gunasekaran, Sidaard, Michael Mongin, Osama A. AlSattam, and Keigo Hirakawa. "Comparison of Event-Based Alogrithms for Experimental Two-Dimensional, Two-Component Velocimetry." Journal of Aircraft (2025): 1-15. https://doi.org/10.2514/1.C038412

Comparison of Event Camera Processing Algorithms for Experimental 2D2C Velocimetry

Students
Michael Mongin
Citation
  • Gunasekaran, Sidaard, Michael Mongin, Osama A. AlSattam, and Keigo Hirakawa. "Comparison of Event Camera Processing Algorithms for Experimental 2D2C Velocimetry." In AIAA SCITECH 2025 Forum, p. 0475. 2025. https://doi.org/10.2514/6.2025-0475

Sensitivity Analysis of Event Based Algorithms for Velocimetry

Students
Abdul Khan
Citation
  • Khan, Abdul R., and Sidaard Gunasekaran. "Sensitivity Analysis of Event Based Algorithms for Velocimetry." In AIAA SCITECH 2026 Forum, p. 1316. 2026. https://doi.org/10.2514/6.2026-1316

Causal Kalman Filtering for Particle Tracking Velocimetry Using an Event Camera

Students
Abdul KhanAndrew KillianMichael Mongin
Citation
  • Khan, Abdul R., Michael P. Mongin, Andrew Killian, Keigo Hirakawa, and Sidaard Gunasekaran. "Causal Kalman Filtering for Particle Tracking Velocimetry Using an Event Camera." Experiments in Fluids (2024).