# Minimal Solvers for Full DoF Motion Estimation from Asynchronous Tracks

arXiv: https://arxiv.org/abs/2508.17537 · HTML: https://mlsanity.com/paper/2508.17537/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 80 references that are in the map.
- First posted on arXiv 24 Aug 2025.

## Builds on (most cited first, 30 of 33)

- [LightGlue: Local Feature Matching at Light Speed](https://mlsanity.com/paper/2306.13643/) (2023)
- [Global Structure-from-Motion Revisited](https://mlsanity.com/paper/2407.20219/) (2024)
- [Toward Geometric Deep SLAM](https://mlsanity.com/paper/1707.07410/) (2017)
- [Rolling-Shutter-Aware Differential SfM and Image Rectification](https://mlsanity.com/paper/1903.03943/) (2019)
- [Rolling Shutter Camera Relative Pose: Generalized Epipolar Geometry](https://mlsanity.com/paper/1605.00475/) (2016)
- [From two rolling shutters to one global shutter](https://mlsanity.com/paper/2006.01964/) (2020)
- [PLMP -- Point-Line Minimal Problems in Complete Multi-View Visibility](https://mlsanity.com/paper/1903.10008/) (2019)
- [Learning Adaptive Warping for Real-World Rolling Shutter Correction](https://mlsanity.com/paper/2204.13886/) (2022)
- [Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution](https://mlsanity.com/paper/2209.08503/) (2022)
- [A 5-Point Minimal Solver for Event Camera Relative Motion Estimation](https://mlsanity.com/paper/2309.17054/) (2023)
- [Direct Sparse Odometry with Rolling Shutter](https://mlsanity.com/paper/1808.00558/) (2018)
- [Motion and Structure from Event-based Normal Flow](https://mlsanity.com/paper/2407.12239/) (2024)
- [USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields](https://mlsanity.com/paper/2310.02687/) (2023)
- [An N-Point Linear Solver for Line and Motion Estimation with Event Cameras](https://mlsanity.com/paper/2404.00842/) (2024)
- [Minimal Solvers for Monocular Rolling Shutter Compensation under Ackermann Motion](https://mlsanity.com/paper/1712.03159/) (2017)
- [Full-DoF Egomotion Estimation for Event Cameras Using Geometric Solvers](https://mlsanity.com/paper/2503.03307/) (2025)
- [Image Stitching and Rectification for Hand-Held Cameras](https://mlsanity.com/paper/2008.09229/) (2020)
- [Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction](https://mlsanity.com/paper/2303.18125/) (2023)
- [Self-supervised Learning to Bring Dual Reversed Rolling Shutter Images Alive](https://mlsanity.com/paper/2305.19862/) (2023)
- [Gyroscope-aided Relative Pose Estimation for Rolling Shutter Cameras](https://mlsanity.com/paper/1904.06770/) (2019)
- [Relative Pose Estimation for Stereo Rolling Shutter Cameras](https://mlsanity.com/paper/2006.07807/) (2020)
- [Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter Video](https://mlsanity.com/paper/2210.03040/) (2022)
- [Inertial-aided Rolling Shutter Relative Pose Estimation](https://mlsanity.com/paper/1712.00184/) (2017)
- [Linear solution to the minimal absolute pose rolling shutter problem](https://mlsanity.com/paper/1812.11532/) (2018)
- [Order-One Rolling Shutter Cameras](https://mlsanity.com/paper/2403.11295/) (2024)
- [Learning Normal Flow Directly From Event Neighborhoods](https://mlsanity.com/paper/2412.11284/) (2024)
- [Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion](https://mlsanity.com/paper/2004.14052/) (2020)
- [URS-NeRF: Unordered Rolling Shutter Bundle Adjustment for Neural Radiance Fields](https://mlsanity.com/paper/2403.10119/) (2024)
- [Monocular Visual Odometry with a Rolling Shutter Camera](https://mlsanity.com/paper/1704.07163/) (2017)
- [Minimal Perspective Autocalibration](https://mlsanity.com/paper/2405.05605/) (2024)

## Built on by (most cited first, 2 of 2)

- [Single-View Rolling-Shutter SfM](https://mlsanity.com/paper/2603.11888/) (2026)
- [Minimal Solvers for Full-DoF Motion Estimation from Asynchronous Differential SfM](https://mlsanity.com/paper/2606.09218/) (2026)

## Abstract (arXiv)

We address the problem of estimating both translational and angular velocity of a camera from asynchronous point tracks, a formulation relevant to rolling shutter and event cameras. Since the original problem is non-polynomial, we propose a polynomial approximation, classify the resulting minimal problems, and determine their algebraic degrees. Furthermore, we develop minimal solvers for several problems with low degrees and evaluate them on synthetic and real datasets. The code will be made publicly available.