Event-based high temporal resolution measurement of shock wave motion field
- URL: http://arxiv.org/abs/2512.22474v1
- Date: Sat, 27 Dec 2025 05:37:18 GMT
- Title: Event-based high temporal resolution measurement of shock wave motion field
- Authors: Taihang Lei, Banglei Guan, Minzu Liang, Pengju Sun, Jing Tao, Yang Shang, Qifeng Yu,
- Abstract summary: Accurate measurement of shock wave motion parameters with high resolution is essential for applications such as power field testing and damage assessment.<n>To address these challenges, a novel framework is proposed that utilizes multiple event cameras to estimate the asymmetry of shock waves.<n>The experimental results demonstrate that our method achieves high-precision measurement of the shock wave motion field with both high spatial and temporal resolution.
- Score: 16.853658330080428
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Accurate measurement of shock wave motion parameters with high spatiotemporal resolution is essential for applications such as power field testing and damage assessment. However, significant challenges are posed by the fast, uneven propagation of shock waves and unstable testing conditions. To address these challenges, a novel framework is proposed that utilizes multiple event cameras to estimate the asymmetry of shock waves, leveraging its high-speed and high-dynamic range capabilities. Initially, a polar coordinate system is established, which encodes events to reveal shock wave propagation patterns, with adaptive region-of-interest (ROI) extraction through event offset calculations. Subsequently, shock wave front events are extracted using iterative slope analysis, exploiting the continuity of velocity changes. Finally, the geometric model of events and shock wave motion parameters is derived according to event-based optical imaging model, along with the 3D reconstruction model. Through the above process, multi-angle shock wave measurement, motion field reconstruction, and explosive equivalence inversion are achieved. The results of the speed measurement are compared with those of the pressure sensors and the empirical formula, revealing a maximum error of 5.20% and a minimum error of 0.06%. The experimental results demonstrate that our method achieves high-precision measurement of the shock wave motion field with both high spatial and temporal resolution, representing significant progress.
Related papers
- Event-based Visual Deformation Measurement [76.25283405575108]
Visual Deformation Measurement aims to recover dense deformation fields by tracking surface motion from camera observations.<n>Traditional image-based methods rely on minimal inter-frame motion to constrain the correspondence search space.<n>We propose an event-frame fusion framework that exploits events for temporally dense motion cues and frames for spatially dense precise estimation.
arXiv Detail & Related papers (2026-02-16T01:04:48Z) - Asynchronous Event Stream Noise Filtering for High-frequency Structure Deformation Measurement [13.890180603359864]
Large-scale structures suffer high-frequency deformations due to complex loads.<n>This paper proposes a method to measure high-frequency deformations by exploiting an event camera and LED markers.
arXiv Detail & Related papers (2025-12-17T03:38:12Z) - Neural reconstruction of 3D ocean wave hydrodynamics from camera sensing [15.737948775422263]
We propose an attention-augmented pyramid architecture tailored to the multi-scale and temporally continuous characteristics of wave motions.<n> Experiments under real-sea conditions demonstrate millimetre-level wave elevation prediction in the central region, dominant-frequency errors below 0.01 Hz, precise estimation of high-frequency spectral power laws, and high-fidelity 3D reconstruction of nonlinear velocity fields.
arXiv Detail & Related papers (2025-12-04T11:23:17Z) - Flexible Gravitational-Wave Parameter Estimation with Transformers [73.44614054040267]
We introduce a flexible transformer-based architecture paired with a training strategy that enables adaptation to diverse analysis settings at inference time.<n>We demonstrate that a single flexible model -- called Dingo-T1 -- can analyze 48 gravitational-wave events from the third LIGO-Virgo-KAGRA Observing Run.
arXiv Detail & Related papers (2025-12-02T17:49:08Z) - Wavefront Curvature and Transverse Atomic Motion in Time-Resolved Atom Interferometry: Impact and Mitigation [0.0]
Time-resolved atom interferometers are used in applications such as gravitational wave detection and searches for ultra-light dark matter.<n>We investigate phase noise arising from shot-to-shot fluctuations in the atoms' transverse motion in the presence of the wavefront curvature of the interferometer beam.
arXiv Detail & Related papers (2025-10-30T17:35:59Z) - Event-based multi-view photogrammetry for high-dynamic, high-velocity target measurement [9.651861391083703]
Existing measurement methods face challenges such as limited dynamic range, discontinuous observations, and high costs.<n>This paper presents a new approach leveraging an event-based multi-view photometric system.<n>In a light gas gun fragment test, the proposed method showed a measurement deviation of 4.47% compared to the electromagnetic speedometer.
arXiv Detail & Related papers (2025-05-31T14:23:39Z) - EMoTive: Event-guided Trajectory Modeling for 3D Motion Estimation [59.33052312107478]
Event cameras offer possibilities for 3D motion estimation through continuous adaptive pixel-level responses to scene changes.<n>This paper presents EMove, a novel event-based framework that models-uniform trajectories via event-guided parametric curves.<n>For motion representation, we introduce a density-aware adaptation mechanism to fuse spatial and temporal features under event guidance.<n>The final 3D motion estimation is achieved through multi-temporal sampling of parametric trajectories, flows and depth motion fields.
arXiv Detail & Related papers (2025-03-14T13:15:54Z) - A 5-Point Minimal Solver for Event Camera Relative Motion Estimation [47.45081895021988]
We introduce a novel minimal 5-point solver that estimates line parameters and linear camera velocity projections, which can be fused into a single, averaged linear velocity when considering multiple lines.
Our method consistently achieves a 100% success rate in estimating linear velocity where existing closed-form solvers only achieve between 23% and 70%.
arXiv Detail & Related papers (2023-09-29T08:30:18Z) - Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion [67.15935067326662]
Event cameras offer low power, low latency, high temporal resolution and high dynamic range.
NeRF is seen as the leading candidate for efficient and effective scene representation.
We propose Robust e-NeRF, a novel method to directly and robustly reconstruct NeRFs from moving event cameras.
arXiv Detail & Related papers (2023-09-15T17:52:08Z) - High-Rate Phase Association with Travel Time Neural Fields [11.935601258042022]
HARPA is a high-rate association framework which incorporates wave physics by leveraging deep generative models and travel time neural fields.<n>It outperforms state-of-the-art association methods for both real seismic data and complex synthetic models.
arXiv Detail & Related papers (2023-07-14T18:29:24Z) - Machine learning for phase-resolved reconstruction of nonlinear ocean
wave surface elevations from sparse remote sensing data [37.69303106863453]
We propose a novel approach for phase-resolved wave surface reconstruction using neural networks.
Our approach utilizes synthetic yet highly realistic training data on uniform one-dimensional grids.
arXiv Detail & Related papers (2023-05-18T12:30:26Z) - Learning Monocular Dense Depth from Events [53.078665310545745]
Event cameras produce brightness changes in the form of a stream of asynchronous events instead of intensity frames.
Recent learning-based approaches have been applied to event-based data, such as monocular depth prediction.
We propose a recurrent architecture to solve this task and show significant improvement over standard feed-forward methods.
arXiv Detail & Related papers (2020-10-16T12:36:23Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.