# SerialTrack: ScalE and Rotation Invariant Augmented Lagrangian Particle Tracking

arXiv: https://arxiv.org/abs/2203.12573 · HTML: https://mlsanity.com/paper/2203.12573/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2022.

## Built on by (most cited first, 3 of 3)

- [GotFlow3D: Recurrent Graph Optimal Transport for Learning 3D Flow Motion in Particle Tracking](https://mlsanity.com/paper/2210.17012/) (2022)
- [Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss](https://mlsanity.com/paper/2410.11934/) (2024)
- [pyALDIC: A Python Implementation of Augmented Lagrangian Digital Image Correlation with a GUI, Adaptive Meshing, and Mask-Aware Subset Splitting](https://mlsanity.com/paper/2607.22755/) (2026)

## Abstract (arXiv)

We present a new particle tracking algorithm to accurately resolve large deformation and rotational motion fields, which takes advantage of both local and global particle tracking algorithms. We call this method the ScalE and Rotation Invariant Augmented Lagrangian Particle Tracking (SerialTrack). This method builds an iterative scale and rotation invariant topology-based feature for each particle within a multi-scale tracking algorithm. The global kinematic compatibility condition is applied as a global augmented Lagrangian constraint to enhance the tracking accuracy. An open source software package implementing this numerical approach to track both 2D and 3D, incremental and cumulative deformation fields is provided.