# Rolling-Shutter-Aware Differential SfM and Image Rectification

arXiv: https://arxiv.org/abs/1903.03943 · HTML: https://mlsanity.com/paper/1903.03943/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Mar 2019.

## Built on by (most cited first, 30 of 32)

- [Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes](https://mlsanity.com/paper/2104.01601/) (2021)
- [SUNet: Symmetric Undistortion Network for Rolling Shutter Correction](https://mlsanity.com/paper/2108.04775/) (2021)
- [Bringing Rolling Shutter Images Alive with Dual Reversed Distortion](https://mlsanity.com/paper/2203.06451/) (2022)
- [Context-Aware Video Reconstruction for Rolling Shutter Cameras](https://mlsanity.com/paper/2205.12912/) (2022)
- [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)
- [NeurOCS: Neural NOCS Supervision for Monocular 3D Object Localization](https://mlsanity.com/paper/2305.17763/) (2023)
- [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)
- [Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty](https://mlsanity.com/paper/2104.08278/) (2021)
- [Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction](https://mlsanity.com/paper/2303.18125/) (2023)
- [Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature](https://mlsanity.com/paper/2204.00974/) (2022)
- [Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter Video](https://mlsanity.com/paper/2210.03040/) (2022)
- [Order-One Rolling Shutter Cameras](https://mlsanity.com/paper/2403.11295/) (2024)
- [Single Image Rolling Shutter Removal with Diffusion Models](https://mlsanity.com/paper/2407.02906/) (2024)
- [Combining Internal and External Constraints for Unrolling Shutter in Videos](https://mlsanity.com/paper/2207.11725/) (2022)
- [URS-NeRF: Unordered Rolling Shutter Bundle Adjustment for Neural Radiance Fields](https://mlsanity.com/paper/2403.10119/) (2024)
- [Instantaneous Perception of Moving Objects in 3D](https://mlsanity.com/paper/2405.02781/) (2024)
- [Single-Scanline Relative Pose Estimation for Rolling Shutter Cameras](https://mlsanity.com/paper/2506.22069/) (2025)
- [Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events](https://mlsanity.com/paper/2304.06930/) (2023)
- [RSL-BA: Rolling Shutter Line Bundle Adjustment](https://mlsanity.com/paper/2408.05409/) (2024)
- [Minimal Solvers for Full DoF Motion Estimation from Asynchronous Tracks](https://mlsanity.com/paper/2508.17537/) (2025)
- [Moment-Reenacting: Inverse Motion Degradation with Cross-shutter Guidance](https://mlsanity.com/paper/2605.22423/) (2026)
- [Deep network for rolling shutter rectification](https://mlsanity.com/paper/2112.06170/) (2021)
- [Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types](https://mlsanity.com/paper/2309.08136/) (2023)
- [Towards High-Frequency Tracking and Fast Edge-Aware Optimization](https://mlsanity.com/paper/2309.00777/) (2023)
- [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)
- [Rolling Shutter Relative Pose Estimation Made Practical](https://mlsanity.com/paper/2606.26863/) (2026)
- [Rolling Shutter Camera Self-Calibration](https://mlsanity.com/paper/2608.01509/) (2026)

## Abstract (arXiv)

In this paper, we develop a modified differential Structure from Motion (SfM) algorithm that can estimate relative pose from two consecutive frames despite of Rolling Shutter (RS) artifacts. In particular, we show that under constant velocity assumption, the errors induced by the rolling shutter effect can be easily rectified by a linear scaling operation on each optical flow. We further propose a 9-point algorithm to recover the relative pose of a rolling shutter camera that undergoes constant acceleration motion. We demonstrate that the dense depth maps recovered from the relative pose of the RS camera can be used in a RS-aware warping for image rectification to recover high-quality Global Shutter (GS) images. Experiments on both synthetic and real RS images show that our RS-aware differential SfM algorithm produces more accurate results on relative pose estimation and 3D reconstruction from images distorted by RS effect compared to standard SfM algorithms that assume a GS camera model. We also demonstrate that our RS-aware warping for image rectification method outperforms state-of-the-art commercial software products, i.e. Adobe After Effects and Apple Imovie, at removing RS artifacts.