# Segmentation of Subspaces in Sequential Data

arXiv: https://arxiv.org/abs/1504.04090 · HTML: https://mlsanity.com/paper/1504.04090/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Apr 2015.

## Built on by (most cited first, 1 of 1)

- [Unsupervised Congestion Status Identification Using LMP Data](https://mlsanity.com/paper/2411.10058/) (2024)

## Abstract (arXiv)

We propose Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Similar to Sparse Subspace Clustering (SSC) we formulate the problem as one of finding a sparse representation but include an additional penalty term to take care of sequential data. We test our method on data drawn from infrared hyper spectral, video and motion capture data. Experiments show that our method, OSC, outperforms the state of the art methods: Spatial Subspace Clustering (SpatSC), Low-Rank Representation (LRR) and SSC.