# Robust Motion Segmentation from Pairwise Matches

arXiv: https://arxiv.org/abs/1905.09043 · HTML: https://mlsanity.com/paper/1905.09043/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2019.

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

- [Quantum Motion Segmentation](https://mlsanity.com/paper/2203.13185/) (2022)
- [Learning To Segment Dominant Object Motion From Watching Videos](https://mlsanity.com/paper/2111.14160/) (2021)
- [Reconstructing Small 3D Objects in front of a Textured Background](https://mlsanity.com/paper/2105.11352/) (2021)

## Abstract (arXiv)

In this paper we address a classification problem that has not been considered before, namely motion segmentation given pairwise matches only. Our contribution to this unexplored task is a novel formulation of motion segmentation as a two-step process. First, motion segmentation is performed on image pairs independently. Secondly, we combine independent pairwise segmentation results in a robust way into the final globally consistent segmentation. Our approach is inspired by the success of averaging methods. We demonstrate in simulated as well as in real experiments that our method is very effective in reducing the errors in the pairwise motion segmentation and can cope with large number of mismatches.