# Color Image Set Recognition Based on Quaternionic Grassmannians

arXiv: https://arxiv.org/abs/2505.23629 · HTML: https://mlsanity.com/paper/2505.23629/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 41 references that are in the map.
- First posted on arXiv 29 May 2025.

## Builds on (most cited first, 4 of 4)

- [Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution](https://mlsanity.com/paper/1310.4891/) (2013)
- [Jumping Manifolds: Geometry Aware Dense Non-Rigid Structure from Motion](https://mlsanity.com/paper/1902.01077/) (2019)
- [Quaternion-based bilinear factor matrix norm minimization for color image inpainting](https://mlsanity.com/paper/2005.02886/) (2020)
- [Grassmannian learning mutual subspace method for image set recognition](https://mlsanity.com/paper/2111.04352/) (2021)

## Abstract (arXiv)

We propose a new method for recognizing color image sets using quaternionic Grassmannians, which use the power of quaternions to capture color information and represent each color image set as a point on the quaternionic Grassmannian. We provide a direct formula to calculate the shortest distance between two points on the quaternionic Grassmannian, and use this distance to build a new classification framework. Experiments on the ETH-80 benchmark dataset and and the Highway Traffic video dataset show that our method achieves good recognition results. We also discuss some limitations in stability and suggest ways the method can be improved in the future.